Measuring fast dynamics in solutions and cells with a laser scanning microscope

Single-point fluorescence correlation spectroscopy (FCS) allows measurements of fast diffusion and dynamic processes in the microsecond-to-millisecond time range. For measurements on living cells, image correlation spectroscopy (ICS) and temporal ICS extend the FCS approach to diffusion times as long as seconds to minutes and simultaneously provide spatially resolved dynamic information. However, ICS is limited to very slow dynamics due to the frame acquisition rate. Here we develop novel extensions to ICS that probe spatial correlations in previously inaccessible temporal windows. We show that using standard laser confocal imaging techniques (raster-scan mode) not only can we reach the temporal scales of single-point FCS, but also have the advantages of ICS in providing spatial information. This novel method, called raster image correlation spectroscopy (RICS), rapidly measures during the scan many focal points within the cell providing the same concentration and dynamic information of FCS as well as information on the spatial correlation between points along the scanning path. Longer time dynamics are recovered from the information in successive lines and frames. We exploit the hidden time structure of the scan method in which adjacent pixels are a few microseconds apart thereby accurately measuring dynamic processes such as molecular diffusion in the microseconds-to-seconds timescale. In conjunction with simulated data, we show that a wide range of diffusion coefficients and concentrations can be measured by RICS. We used RICS to determine for the first time spatially resolved diffusions of paxillin-EGFP stably expressed in CHOK1 cells. This new type of data analysis has a broad application in biology and it provides a powerful tool for measuring fast as well as slower dynamic processes in cellular systems using any standard laser confocal microscope.     

Fluorescence correlation spectroscopy in small cytosolic compartments depends critically on the diffusion model used

Fluorescence correlation spectroscopy (FCS) is a powerful technique for measuring low concentrations of fluorescent molecules and their diffusion constants. In the standard case, fluorescence fluctuations are measured in an open detection volume defined by the confocal optics. However, if FCS measurements are carried out in cellular processes that confine the detection volume, the standard FCS model leads to erroneous results. In this paper, we derive a modified FCS model that takes into account the confinement of the detection volume. Using this model, we have carried out the first FCS measurements in dendrites of cultured neurons. We further derive, for the case of confined diffusion, the limits within which the standard two- and three-dimensional diffusion models give reliable results.     

Fluorescence correlation spectroscopy diffusion laws to probe the submicron cell membrane organization

To probe the complexity of the cell membrane organization and dynamics, it is important to obtain simple physical observables from experiments on live cells. Here we show that fluorescence correlation spectroscopy (FCS) measurements at different spatial scales enable distinguishing between different submicron confinement models. By plotting the diffusion time versus the transverse area of the confocal volume, we introduce the so-called FCS diffusion law, which is the key concept throughout this article. First, we report experimental FCS diffusion laws for two membrane constituents, which are respectively a putative raft marker and a cytoskeleton-hindered transmembrane protein. We find that these two constituents exhibit very distinct behaviors. To understand these results, we propose different models, which account for the diffusion of molecules either in a membrane comprising isolated microdomains or in a meshwork. By simulating FCS experiments for these two types of organization, we obtain FCS diffusion laws in agreement with our experimental observations. We also demonstrate that simple observables derived from these FCS diffusion laws are strongly related to confinement parameters such as the partition of molecules in microdomains and the average confinement time of molecules in a microdomain or a single mesh of a meshwork.     

Measuring antibody affinity and performing immunoassay at the single molecule level

Fluorescence correlation spectroscopy (FCS) enables direct observation of the translational diffusion of single fluorescent molecules in solution. When fluorescent hapten binds to antibody, analysis of FCS data yields the fractional amounts of free and bound hapten, allowing determination of the equilibrium binding constant. Equilibrium dissociation constants of anti-digoxin antibodies and corresponding fluorescein-labeled digoxigenin obtained by FCS and fluorescence polarization measurements are identical. It is also possible to follow a competitive displacement of the tracer from the antibody by unlabeled hapten using FCS in an immunoassay format. The fluorescence polarization immunoassay for vancomycin detection was used to test the FCS approach. Fitting of the FCS data for the molar fractions of free and bound fluorescein-labeled vancomycin yielded a calibration curve which could serve for determination of the vancomycin concentration in biological samples.     

Fluorescence correlation spectroscopy and quantitative cell biology

Fluorescence correlation spectroscopy (FCS) analyzes fluctuations in fluorescence within a small observation volume. Autocorrelation analysis of FCS fluctuation data can be used to measure concentrations, diffusion properties, and kinetic constants for individual fluorescent molecules. Photon count histogram analysis of fluorescence fluctuation data can be used to study oligomerization of individual fluorescent molecules. If the FCS observation volume is positioned inside a living cell, these parameters can be measured in vivo. FCS can provide the requisite quantitative data for analysis of molecular interaction networks underlying complex cell biological processes.     

Correlation spectroscopy of minor fluorescent species: signal purification and distribution analysis

We are performing experiments that use fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) to monitor the movement of an individual donor-labeled sliding clamp protein molecule along acceptor-labeled DNA. In addition to the FRET signal sought from the sliding clamp-DNA complexes, the detection channel for FRET contains undesirable signal from free sliding clamp and free DNA. When multiple fluorescent species contribute to a correlation signal, it is difficult or impossible to distinguish between contributions from individual species. As a remedy, we introduce "purified FCS", which uses single molecule burst analysis to select a species of interest and extract the correlation signal for further analysis. We show that by expanding the correlation region around a burst, the correlated signal is retained and the functional forms of FCS fitting equations remain valid. We demonstrate the use of purified FCS in experiments with DNA sliding clamps. We also introduce "single-molecule FCS", which obtains diffusion time estimates for each burst using expanded correlation regions. By monitoring the detachment of weakly-bound 30-mer DNA oligomers from a single-stranded DNA plasmid, we show that single-molecule FCS can distinguish between bursts from species that differ by a factor of 5 in diffusion constant.     

Fluorescence correlation spectroscopy for the study of membrane dynamics and protein/lipid interactions

Fluorescence correlation spectroscopy (FCS) is a powerful technique to study dynamic biomolecular processes. It allows the estimation of concentrations, diffusion coefficients, molecular interactions, and other processes causing fluctuations in the fluorescence intensity, thus yielding information about aggregation processes, enzymatic reactions, or partition coefficients. During the last years, FCS has been successfully applied to model and cellular membranes, proving to be a promising tool for the study of membrane dynamics and protein/lipid interactions. Here we describe the theoretical basis of FCS and some practical implications for its application in membrane studies. We discuss sources of potential artifacts, such as membrane undulations, positioning of the detection volume, and photobleaching. Special attention is paid to aspects related to instrumentation and sample preparation as well as data acquisition and analysis. Finally, we comment on some strategies recently developed for the specific improvement of FCS measurements on membranes.     

Lateral Membrane Diffusion Modulated by a Minimal Actin Cortex

Diffusion of lipids and proteins within the cell membrane is essential for numerous membrane-dependent processes including signaling and molecular interactions. It is assumed that the membrane-associated cytoskeleton modulates lateral diffusion. Here, we use a minimal actin cortex to directly study proposed effects of an actin meshwork on the diffusion in a well-defined system. The lateral diffusion of a lipid and a protein probe at varying densities of membrane-bound actin was characterized by fluorescence correlation spectroscopy (FCS). A clear correlation of actin density and reduction in mobility was observed for both the lipid and the protein probe. At high actin densities, the effect on the protein probe was ∼3.5-fold stronger compared to the lipid. Moreover, addition of myosin filaments, which contract the actin mesh, allowed switching between fast and slow diffusion in the minimal system. Spot variation FCS was in accordance with a model of fast microscopic diffusion and slower macroscopic diffusion. Complementing Monte Carlo simulations support the analysis of the experimental FCS data. Our results suggest a stronger interaction of the actin mesh with the larger protein probe compared to the lipid. This might point toward a mechanism where cortical actin controls membrane diffusion in a strong size-dependent manner.     

Measuring Mobility in Chromatin by Intensity-Sorted FCS

The architectural organization of chromatin can play an important role in genome regulation by affecting the mobility of molecules within its surroundings via binding interactions and molecular crowding. The diffusion of molecules at specific locations in the nucleus can be studied by fluorescence correlation spectroscopy (FCS), a well-established technique based on the analysis of fluorescence intensity fluctuations detected in a confocal observation volume. However, detecting subtle variations of mobility between different chromatin regions remains challenging with currently available FCS methods. Here, we introduce a method that samples multiple positions by slowly scanning the FCS observation volume across the nucleus. Analyzing the data in short time segments, we preserve the high temporal resolution of single-point FCS while probing different nuclear regions in the same cell. Using the intensity level of the probe (or a DNA marker) as a reference, we efficiently sort the FCS segments into different populations and obtain average correlation functions that are associated to different chromatin regions. This sorting and averaging strategy renders the method statistically robust while preserving the observation of intranuclear variations of mobility. Using this approach, we quantified diffusion of monomeric GFP in high versus low chromatin density regions. We found that GFP mobility was reduced in heterochromatin, especially within perinucleolar heterochromatin. Moreover, we found that modulation of chromatin compaction by ATP depletion, or treatment with solutions of different osmolarity, differentially affected the ratio of diffusion in both regions. Then, we used the approach to probe the mobility of estrogen receptor-α in the vicinity of an integrated multicopy prolactin gene array. Finally, we discussed the coupling of this method with stimulated emission depletion FCS for performing FCS at subdiffraction spatial scales.     

Quantitative Analysis of Single Particle Trajectories: Mean Maximal Excursion Method

An increasing number of experimental studies employ single particle tracking to probe the physical environment in complex systems. We here propose and discuss what we believe are new methods to analyze the time series of the particle traces, in particular, for subdiffusion phenomena. We discuss the statistical properties of mean maximal excursions (MMEs), i.e., the maximal distance covered by a test particle up to time t. Compared to traditional methods focusing on the mean-squared displacement we show that the MME analysis performs better in the determination of the anomalous diffusion exponent. We also demonstrate that combination of regular moments with moments of the MME method provides additional criteria to determine the exact physical nature of the underlying stochastic subdiffusion processes. We put the methods to test using experimental data as well as simulated time series from different models for normal and anomalous dynamics such as diffusion on fractals, continuous time random walks, and fractional Brownian motion.     

Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments.     

RNA dimerization monitored by fluorescence correlation spectroscopy

Fluorescence correlation spectroscopy (FCS) provides a versatile tool to investigate molecular interaction under native conditions, approximating infinite dilution. One precondition for its application is a sufficient difference between the molecular weights of the fluorescence-labelled unbound and bound ligand. In previous studies, an 8-fold difference in molecular weights or correspondingly a 1.6-fold difference in diffusion coefficients was required to accurately distinguish between two diffusion species by FCS. In the presented work, the hybridization of two complementary equally sized RNA single strands was investigated at an excellent signal-to-noise ratio enabled by the highly photostable fluorophore Atto647N. The fractions of ssRNA and dsRNA were quantified by applying multicomponent model analysis of single autocorrelation functions and globally fitting several autocorrelation functions. By introducing a priori knowledge into the fitting procedure, 1.3- to 1.4-fold differences in diffusion coefficients of single- and double-stranded RNA of 26, 41, and 54 nucleotides could be accurately resolved. Global fits of autocorrelation functions of all titration steps enabled a highly accurate quantification of diffusion species fractions and mobilities. At a high signal-to-noise ratio, the median of individually fitted autocorrelation functions allowed a robust representation of heterogeneous data. These findings point out the possibility of studying molecular interaction of equally sized molecules based on their diffusional behavior, which significantly broadens the application spectrum of FCS.     

A new approach for fluorescence correlation spectroscopy (FCS) based immunoassays

Fluorescence correlation spectroscopy (FCS) is a powerful technique for measuring physicochemical properties, such as concentration and diffusion constant, of bio-molecules in complex mixtures. Although, as such, FCS is well suited for development of homogeneous immunoassays, a major obstacle lies in the relatively high molecular weight of antibodies. This is because in FCS discrimination between unbound fluorescently-labelled antibodies and the same antibodies bound to immune complexes is based on the difference of their respective diffusion coefficients. To overcome this limitation we here propose to use a fluorescently-labelled tag which has two crucial properties: (a) its molecular weight is significantly lower than that of an antibody and (b) it is capable to discriminate between free antibodies and immune complexes. We have evaluated the feasibility of this approach in a model system consisting of mouse monoclonal IgG directed against the Lewis X antigen, and Protein A as a low molecular weight tag.     

Characterizing diffusion dynamics of a membrane protein associated with nanolipoproteins using fluorescence correlation spectroscopy

Nanolipoprotein particles (NLPs) represent a unique nanometer-sized scaffold for supporting membrane proteins (MP). Characterization of their dynamic shape and association with MP in solution remains a challenge. Here, we present a rapid method of analysis by fluorescence correlation spectroscopy (FCS) to characterize bacteriorhodopsin (bR), a membrane protein capable of forming a NLP complex. By selectively labeling individual components of NLPs during cell-free synthesis, FCS enabled us to measure specific NLP diffusion times and infer size information for different NLP species. The resulting bR-loaded NLPs were shown to be dynamically discoidal in solution with a mean diameter of 7.8 nm. The insertion rate of bR in the complex was ～55% based on a fit model incorporating two separate diffusion properties to best approximate the FCS data. More importantly, based on these data, we infer that membrane protein associated NLPs are thermodynamically constrained as discs in solution, while empty NLPs appear to be less constrained and dynamically spherical.     

Fluorescence correlation spectroscopy detects galanin receptor diversity on insulinoma cells

Fluorescence correlation spectroscopy (FCS) allows the study of interactions of fluorescently labeled ligand with receptors in living cells at single-molecule detection sensitivity. From the autocorrelation functions of fluorescence intensity fluctuations, the diffusion time of molecules through the confocal volume is analyzed, and from that, the molecular weights of free and bound molecules can be calculated. We have applied FCS to study the receptor diversity for the neuropeptide galanin (GAL) in cultured cells. FCS measurement of the fluorophore rhodamine-labeled GAL (Rh-GAL) has been performed in 0.2-fL confocal volume elements of the laser beam. The analysis of autocorrelation functions of Rh-GAL in solution above cells and at cell membranes demonstrates that the diffusion time of unbound Rh-GAL is 0.16 ms, whereas diffusion times of membrane-bound Rh-GAL are 22 and 700 ms. Because both of the diffusion times (22 and 700 ms) are much longer as compared to that of unbound Rh-GAL, they correspond to slow-diffusing complexes when Rh-GAL is bound to the cell membranes. Addition of excess nonlabeled GAL is accompanied by competitive displacement. Full saturation of the GAL binding is obtained at nanomolar concentrations. Scatchard analysis of binding data reveal one binding process, assuming one binding site per Rh-GAL (n = 1). On the other hand, the appearance of two diffusion times, 22 and 700 ms, suggests the existence of two subpopulations of GAL receptor complexes or two subtypes of GAL receptor not detected before. This makes an important point that FCS permits the identification of receptors, which were not possible to detect before by conventional binding techniques. The inhibitory effect of pertussis toxin on the GAL binding considers a G-protein-involved allosteric system, important for the clarification of essential steps in the G-protein-related signal transduction. This study is of pharmaceutical significance, since it will provide insights into how FCS can be used as a rapid technique for studying ligand-receptor interactions in living cells, which is one step forward for large-scale drug screening in cell cultures.     

Anomalous protein diffusion in living cells as seen by fluorescence correlation spectroscopy

We investigate the challenges and limitations that are encountered when studying membrane protein dynamics in vivo by means of fluorescence correlation spectroscopy (FCS). Based on theoretical arguments and computer simulations, we show that, in general, the fluctuating fluorescence has a fractal dimension D(0) >or= 1.5, which is determined by the anomality alpha of the diffusional motion of the labeled particles, i.e., by the growth of their mean square displacement as (Deltax)(2) approximately t(alpha). The fractality enforces an initial power-law behavior of the autocorrelation function and related quantities for small times. Using this information, we show by FCS that Golgi resident membrane proteins move subdiffusively in the endoplasmic reticulum and the Golgi apparatus in vivo. Based on Monte Carlo simulations for FCS on curved surfaces, we can rule out that the observed anomalous diffusion is a result of the complex topology of the membrane. The apparent mobility of particles as determined by FCS, however, is shown to depend crucially on the shape of the membrane and its motion in time. Due to this fact, the hydrodynamic radius of the tracked particles can be easily overestimated by an order of magnitude.     

Quantitative fluorescence imaging of protein diffusion and interaction in living cells

Diffusion processes and local dynamic equilibria inside cells lead to nonuniform spatial distributions of molecules, which are essential for processes such as nuclear organization and signaling in cell division, differentiation and migration. To understand these mechanisms, spatially resolved quantitative measurements of protein abundance, mobilities and interactions are needed, but current methods have limited capabilities to study dynamic parameters. Here we describe a microscope based on light-sheet illumination that allows massively parallel fluorescence correlation spectroscopy (FCS) measurements and use it to visualize the diffusion and interactions of proteins in mammalian cells and in isolated fly tissue. Imaging the mobility of heterochromatin protein HP1α (ref. 4) in cell nuclei we could provide high-resolution diffusion maps that reveal euchromatin areas with heterochromatin-like HP1α-chromatin interactions. We expect that FCS imaging will become a useful method for the precise characterization of cellular reaction-diffusion processes.