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Fluorescence correlation spectroscopy is a single-molecule fluorescence technique used to monitor molecular dynamics. When applied to living cells, FCS has been used to decipher the diffusion times of protein and lipid molecules, to determine the concentrations of a particular molecule at a specific cellular location, to determine kinetic parameters such as on/off rates constants and binding coefficients for protein/protein interactions .
The basic principle for FCS is that a fluorescent molecule emits photons while moving through a confocal volume illuminated by a laser (Figure 1). The number of photons that can be collected from the confocal volume depends on the diffusion time of the fluorescent molecules (which is a function of the mass of the molecule), the concentration of molecules, the quantum yield of the fluorophore attached to the molecule and finally the size of the illuminated volume, which is dependent on the instrument . Typically a small diffraction limited confocal volume of 0.3μm × 1μm (~size of an E. coli) is excited with a laser beam and then the emitted photons are collected and counted on a photodiode detector. These measurements are then used to calculate and display autocorrelation and cross correlation functions, coincidence diagrams, photon count histograms, count rate diagrams and pulse density histograms from which diffusion times, on/off rates etc can be extracted using data fitting and modeling software .
In this protocol, we present the basic design of an FCS measurement in living cells, and address critical issues in experiment design (from the choice of dyes or cells to data analysis). The user must be aware that FCS requires subsequent adjustments in the experimental design as well as the data analysis to address successfully specific biological questions. Comments after the basic protocol will present classic pitfalls and troubleshooting tips to help this.
Below will be the steps outlined for the Zeiss LSM Confocor 3 FCS system, one of the more popular turnkey FCS systems in the market. For others, the step-by step instructions may vary.
The most difficult task in a successful FCS measurement is the fitting and interpretation of the collected data. Although these are common tasks of any experimental measurement, there are few issues that are specific for FCS and that need to be addressed in this section.
As we pointed out in the introduction, FCS monitors any fluctuation of fluorescence within the confocal volume. Typically, any variation of fluorescence on time scales from 1μs to 1s will generate a relaxation in the autocorrelation curve that must be fitted and interpreted. To successfully process the data, the experimenter must derive an analytical formula accounting for all fluctuations. For FCS in living cells, these analytical fits may be hard to derive: that leaves the experimenter with hard-to-interpret phenomenological time scales that are still sufficient for an analytical assay in perturbation experiment (comparison of wild-type and drug-treated or gene-perturbed cells).
where N is the average number of fluorescent objects within the confocal volume, τD the correlation time τD=ω2/4/D where D is the diffusion coefficient of the fluorescent object and ω is the radial diameter of the confocal volume. The LSR510-Confocor software offers to use a theoretically more accurate diffusion fit including the longitudinal diffusion. But, a 3D formula does not improve the statistical accuracy of the fit, and requires careful calibration of the longitudinal dimension of the confocal volume to be valuable. A typical curve for soluble GFP diffusing with a cell cytoplasm is presented in Figure 2
where Ni is the average number of fluorescent objects labeled i within the confocal volume, τ0=w2/4/Di where Di is the diffusion coefficient of the fluorescent object labeled i and w is the radial diameter of the confocal volume. Note that the more difference there is between the diffusion of the fluorescent objects, the better the fit of the data.
In many living cell settings, the diffusion of fluorescence objects encompasses multi-scale, multi-timescale moves. An explicit description of such a convoluted process is formally impossible, and experimenters routinely use phenomenological “stretched diffusion” formula to fit the FCS data. An example of such a fit was used in :
where N is the average number of fluorescent objects within the confocal volume, τD is a characteristic diffusion timescale, and α is the stretching parameter (with 0< α <1). The smaller α the more convoluted the diffusion is.
where N is the average number of fluorescent objects within the confocal volume, τ0 is the characteristic diffusion timescale, and τR is the characteristic chemical-relaxation timescale. Note that for a simple on-off with characteristic chemical rates kon and koff,
In practice, the dynamic range for the FCS autocorrelation amplitude β is too small to yield an accurate estimate of K: a separate measurement is then required.
More generally, the analytical fits used to analyze FCS measurements can get complicated by the rich dynamics of a system (e.g. ). There are reviews documenting different applications with different fitting functions for FCS measurements in living cells [2, 10].
Here, we present a typical FCS curve for diffusing fluorescently-tagged molecules within the cytoplasm of a living cell, and the associated fit to help FCS users understand what each parameter mean (see Figure 3). Typically, the fit is:
Confocor fitting software generates a table with the following parameters:
Count rate [kHz] = total number of photons collected by a detector per second.
Correlation = amplitude of the correlation function G(0).
Counts per molecule [kHz] = is computed as (Count rate)*(G(0) - 1). This parameter can be very useful to estimate the state of aggregation of a fluorescent protein
Amplitude Number particles = Ni (note that when the triplet fraction p is negligible).
Triplet state Fraction [% ]: p*100.
Triplet state Relaxation time [μs] = τT.
Component i Fraction [%] =
Component i Diffusion time [μs]: τi,
Translation Structural parameter: this parameter should be fixed upon calibration of the optical setup (See Note 5). It corresponds to the aspect ratio of the confocal volume, defined as the ratio of its longitudinal direction with the transversal dimension. Typically this parameter should be set around 10.
Optimizing an FCS measurement implies optimizing the actual number of photons collected from individual fluorescent object. This parameter can be obtained from the countrate/molecule in the LSM510-Confocor software.
Typically, for GFP in living cells, with 1% of the 488nm lane of a 40mWatt Argon laser, and a collection pinhole at 70μM, one should obtain typically 15,000 photons per second (15 kHz / molecule). Once the experimental system (with a chosen fluorophore) has been configured, only three parameters [the optical alignment, the laser excitation, and the acquisition time] need to be optimized by the experimenter. LSM510-Confocor allows the experimenter to automatically align the acquisition pinhole (in x and y directions) based on maximization of collected fluorescence. The z-alignment is more difficult to optimize but factory settings are usually sufficient. The experimenter should then increase the laser intensity until fluorescence photobleaching becomes prevalent (this can be detected by seeing a non-flat baseline at long lagtimes, Figure 4). Finally, the experimenter should then increase the acquisition time to allow (the trade-off being photobleaching in the spot of interest).
Note that the number of photons collected from individual fluorophores maybe limited by the saturation of the photoreceptors (theoretically 5 million counts per second, practically 1 million photons per second). Thus there are intrinsic limitations on the concentration of fluorescent objects per confocal volume that is compatible with sufficient photon collection for FCS. Typically, if one would like to collect at a count rate of 5000/s/molecule, there will be atmost 200 molecules in a confocal volume of typically 1fl, hence the maximum concentration of fluorescent objects in this experiment would be 0.4μMol. Hence is the need to select lower-expressing cells or pre-bleach the samples.
Photobleaching of the fluorophore under consideration should not be a concern in FCS experiments when relaxation timescales below 50ms are under consideration (typical for proteins diffusing in the cytoplasm). However, for membrane proteins or for proteins bound to large biological objects (vesicles, mitochondria etc.), residency time within every confocal volume gets larger than 50ms, and one should pay special attention to the issue of photobleaching.
In typical FCS application in living cells, photobleaching appears as a large decay in the autocorrelation function with typical timescales between 100ms and 10s (Figure 4). To maintain the statistical relevance of data fitting, one must make sure that the autocorrelation baseline at long lag times is flat. The rule of thumb is then to obtain at least half a decade of flat baseline at 1.0 to be secured that photobleaching will not be an issue in the analysis of the autocorrelation function. A second rule to experimentally-control for photobleaching consists in repeating every FCS measurement with increased laser excitation: if photobleaching is irrelevant, the overall shape of the autocorrelation function should not be affected by the change in laser intensity.
In some experiments, one would like to gain information about faster fluorescence fluctuations (with timescales below 100μs compared to typical diffusion events above 100us), in particular, to study GFP dynamics and gain information on pH environment in living cells, or to study small fluorophore diffusion. In that range of timescales, one must pay attention to potential artefacts due to the fluorophore internal dynamics or detector limitations.
Fluorophore internal dynamics in the 10μs -100μs range as measured by FCS can be informative of the biological environment (e.g. monitoring GFP quenching at low pH). On the other hand, triplet formation (a situation where the fluorophore goes from a singlet-excitable state to a triplet-quenched state) occurs with timescales between 1μs and 10μs (Figure 5). An easy solution to control for potential excitation-induced dynamics is to check the consistency of the FCS measurements for different laser intensities. Note that diffusion timescales will increase slightly as laser intensity is increased because of an increase of excitation volume.
Triplet formation is a problem encountered mostly with inorganic dyes (e.g. FITC) at high laser intensity. GFP and other naturally-fluorescent proteins have very low triplet conversion probability . It is not recommended to use the LSM510-Confocor to decipher sub-microsecond fluctuation dynamics as detector after pulsing introduces a highly correlated signal in the autocorrelation curve in that time range .
In the Zeiss Confocor 3 as well as the Leica FCS2, scanner mirrors of the confocal microscope are used for precise positioning, ensuring that the correlation spectra are recorded from the exact locations marked on the images scanned. However it is still good practice to check for any offset between the Scanners and the FCS stage positioning, especially if precision is needed <100nm in x and y. To determine the offset one can use a macro (available on the Zeiss or Leica instruments) or do it manually with an ‘ad hoc’ procedure to insure that the two confocal volumes from which fluorescence is collected are exactly aligned, such that confocal imaging and FCS measurements are in registry. Note that misregistry along the z axis is rather unlikely as this optical alignment does not vary much from the factory-settings: only x and y alignments need to be performed (before every FCS session).
To perform offset compensation with a macro, follow directions in instrument manual.
1The absence of phenol red pH-indicator (commonly used in tissue culture media) helps to minimize the levels of background fluorescence during FCS.
2There are several options for temperature control of the microscope stage. A Nevtek Airstream incubator ASI 400 (Nevtek Corp., USA) in combination with a digital thermometer with a thermocouple (Omega Instruments, USA) whose temperature sensor is attached to the head of the condenser or to a site on the stage adjacent to the cell chamber is a convenient set-up for holding steady temp (+/- 0.5 degrees Celsius) in most applications requiring imaging up to 12 hours  . It also allows easy access to the cell chamber for adding reagents into the cells in the course of the experiment while they are on the stage, without shaking the cell chamber or stage, both of which could result in the loss of the position of the cell being imaged. The drawback is that because of exposure to ambient CO2 and humidity and the usual degradation of the buffer, over time the media will gradually evaporate and become basic in pH. If long-term maintenance of cells is necessary then it is advisable to invest in a closed chamber set-up, one that even encloses the microscope stage and optics.
3The XY scan pinhole should be adjusted to give you a high-resolution image, typically ~1 Airy unit. To go below 1 Airy unit is usually not recommended since there is very little resolution gained to compensate for the significant loss in light collection from the sample.
4Longer acquisitions from a single marked site will allow for more statistical information for long lagtimes (t>1s). This will benefit the curve fitting but it may also result in increased bleaching of the sample. Typical acquisition times are 10 seconds. In the acquisition menu one can also introduce a pre bleach time prior to FCS acquisition. Here the sample will be photobleached for a discrete amount of time before recording correlation. This is useful if the sample fluorescence is too high. Always perform measurements a second time with 5Xtimes higher power to check consistency with power amplitude.
5To calibrate the size of the confocal volume, perform a FCS measurement on a solution of fluorescent dye (e.g. Oregon Green) at a known concentration c. Measure the Amplitude Number of particles (N) in the FCS measurement. Then, where Na=6.02×1023 is the Avogadro number.
In particular, this will enable you to calibrate the Translational Structure Parameter (TSM) as: