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Dear Jammi,

Calculating a diffusion coefficient from an FRAP experiment is usually based
on the fitting of a particular FRAP model to the experimental fluorescence
recovery curve. Therefore, to obtain a valid diffusion coefficient, it is of
utmost importance that your experiment is carried out according to the
theory of the FRAP model you want to use.

Apart from a few exceptions, most FRAP models indeed assume an instantaneous
photobleaching phase, which in fact is the assumption of having no recovery
while photobleaching. Hence, the the time for photobleaching should be very
short (< 5%) compared to your experiment's characteristic recovery time. In
actual practice this means that in most cases you can only use one bleaching
iteration (although it depends on many parameters: scanning speed, bleach
geometry, diffusion speed). For longer photobleaching times you will get the
'corona' effect you mentioned, leading in fact to a decreased (not
increased) diffusion coefficient.

As long as you respect this simple but important rule, the actual percentage
of photobleaching doesn't matter, at least if you are using a good FRAP
model. With 'good' I mean a FRAP model which takes the amount of
photobleaching explicitly into account. For such a FRAP model you can
include this 'photobleaching parameter' as a free fitting variable to obtain
its value for each experiment from a fitting to the data.

For completeness sake I should mention that there are FRAP models which do
not require an instantaneous photobleaching phase (see list below). One is
based on Fourier transforms, the other on a statistical analysis. The
Fourier method is very neat in theory, but doesn't seem to work very well in
actual practice based on our own experience because it is very noise
sensitive. Does anyone of the Confocal List have a different experience with
this?

Finally, there are also empirical FRAP methods which are based on the idea
that if one does exactly the same in each sample (same bleach intensity,
bleach time and bleach geometry) one can get a relative diffusion
coefficient by comparing the recovery-half-times. While this sounds a
reasonable assumption in theory, I wouldn't recommend it because in actual
practice you will not get the same photobleaching result in different
samples, as you have observed for yourself in your own experiments. The main
reason for this is that the photobleaching process is based on photochemical
reactions in which many different molecules play a role. So for example, in
a high viscosity sample you will get less photobleaching compared to a
similar low viscosity sample because in the latter the molecules are
diffusing more rapidly, hence increasing the number of photobleaching
reactions per second, hence leading to more photobleaching. And things
become even more complicated when doing measurements in different regions of
a cell where the chemical environment can differ as well.

So as you can see it all comes down to which FRAP model you will be using
for calculating the diffusion coefficient. In case you have not decided yet
which model to use, below is a (non exhautive) list of possible FRAP
models/methods.

Hopefully this is of help to you.

Best regards,

Kevin Braeckmans, Ph.D.
Lab. General Biochemistry and Physical Pharmacy
Ghent University
Belgium


Here's the list.

1. Axelrod, D., D.E. Koppel, J. Schlessinger, J. Elson, and W.W. Webb. 1976.
Mobility measurement by analysis of fluorescence photobleaching recovery
kinetics. Biophys. J. 16:1055-1069.

This fundamental article covers 2D diffusion and 1D flow for Gaussian and
uniform spot photobleaching. A more practical expression for uniform spot
photobleaching has been derived by:

2. Soumpasis, D.M. 1983. Theoretical analysis of fluorescence photobleaching
recovery experiments. Biophys. J. 41:95-97.

FRAP in 2D with the uniform spot method has been examined for 2 diffusing
components as well:

3. Gordon, G.W., B. Chazotte, X.F. Wang, and B. Herman. 1995. Analysis of
simulated and experimental fluorescence recovery after photobleaching. Data
for two diffusing components. Biophys. J. 68:766-778.

A paper discribing FRAP for a Gaussian spot in case of second order
photobleaching kinetics:

4. Bjarneson, D. W., and N. O. Petersen. 1991. Effects of second order
photobleaching on recovered diffusion parameters from fluorescence
photobleaching recovery. Biophys. J. 60:1128-1131.

A 3D extension of the Gaussian spot has been proposed by:

5. Blonk, J.C.G., A. Don, H. Van Aalst, and J.J. Birmingham. 1993.
Fluorescence photobleaching recovery in the confocal scanning light
microscope. J. Microsc. 169:363-374.

And a similar 3D extension of the uniform spot was recently derived by us.
The model is also applicable to bleaching disk-shaped geometries on confocal
scanning microscopes:

6. Braeckmans, K., L. Peeters, N. N. Sanders, S. C. De Smedt, and J.
Demeester. 2003. Three-dimensional fluorescence recovery after
photobleaching with the confocal microscope. Biophys. J. 85:2240-2252.

A numerical approach for the 2D uniform spot (or disk) has been presented
by:

7. Lopez, A., L. Dupou, A. Altibelli, J. Trotard, and J. Tocanne. 1988.
Fluorescence recovery after photobleaching (FRAP) experiments under
conditions of uniform disk illumination. Biophys. J. 53:963-970.

A numerical approach for 2D FRAP in a diffraction limited line segment was
developed by:

8. Wedekind, P., U. Kubitscheck, O. Heinrich, and R. Peters. 1996.
Line-Scanning microphotolysis for diffraction-limited measurements of
lateral diffusion. Biophys. J. 71:1621-1632.

and later in 3D as well:

9. Kubitscheck, U., P. Wedekind, and R. Peters. 1998. Three-dimensional
diffusion measurements by scanning microphotolysis. J. Microsc. 192:126-138.

A statistical evaluation of 2D FRAP for arbitrary radially symmetric
bleaching geomteries has been presented as well. This method has the
advantage of being independent of the bleaching kinetics and possible
recovery during bleaching. A disadvantage is that it does not allow to
calculate the immobile fraction independently.

10. Kubitscheck, U., P. Wedekind, and R. Peters. 1994. Lateral diffusion
measurements at high spatial resolution by scanning microphotolysis in a
confocal microscope. Biophys. J. 67:948-956.

A method for 2D FRAP having essentially the same advantages and
disadvantages, relies on a calculation involving Fourier transforms of the
recovery images. An additional advantage is that the bleaching geometry is
completely arbitrary. The following two articles explain how the technique
works:

11. Tsay, T., and K.A. Jacobson. 1991. Spatial Fourier analysis of video
photobleaching measurements, principles and optimization. Biophys. J.
60:360-368.

which should be read in combination with

12. Berk, D.A., F. Yuan, M. Leunig, and R. K. Jain. 1993. Fluorescence
photobleaching with spatial Fourier analysis: measurement of diffusion in
light-scattering media. Biophys. J. 65:2428-2436.

A method for the analysis of a distribution of diffusion coefficients (in
stead of just 1 or 2) has been described by:

13. Periasamy, N., and A. S. Verkman. 1998. Analysis of fluorophore
diffusion by continuous distributions of diffusion coefficients: Application
to photobleaching measurements of multicomponent and anomalous diffusion.
Biophys. J. 75:557-567.

A method for measuring relative diffusion coefficients by FRAP:

14. Kao, H. P., J. R. Abney, and A. S. Verkman. 1993. Determinants of the
translational mobility of a small solute in cell cytoplasm. J. Cell Biol.
120:175-184.

and later articles by the same authors. For a review of their methods see:
Verkman, A. S. 2003. Diffusion in cells measured by flourescence recovery
after photobleaching. In Biophotonics, Part A: Methods in Enzymology, Volume
360. G. Marriott and I. Parker, editors. Academic Press, New York,
pp.635-648.

1D FRAP in a limited volume based on Fourier transforms was derived by:

15. Elowitz,M.B.; Surette,M.G.; Wolf,P.E.; Stock,J.B.; Leibler,S. 1999.
Protein mobility in the cytoplasm of Escherichia coli. J. Bacteriology.
181:197-203.

A FRAP model for 1D diffusion including association and dissociation:

16. Carrero, G., D. McDonald , E. Crawford, G. de Vries, and M. J. Hendzel.
2003. Using FRAP and mathematical modeling to determine the in vivo kinetics
of nuclear proteins. Methods 29:14-28.

A paper describing a 'Fringe Pattern Photobleaching and Recovery' method, as
well as a FRAP method relying on a uniformly bleached long line segment:

17. Cheng, Y., R. K. Prud'homme, and J. L. Thomas. 2002. Diffusion of
mesoscopic probes in aqueous polymer solutions measured by fluorescence
recovery after photobleaching. Macromolecules 35:8111-8121.

An other paper describing FRAP in case of a long line segment:

18. Dietrich, C., R. Merkel, and R. Tampe. 1997. Diffusion measurement of
fluorescence-labeled amphiphilic molecules with a standard fluorescence
microscope. Biophys. J. 72:1701-1710.

A recent paper describing a FRAP technique using continuous spot
photobleaching allowing to calculate dissociation and residence times at
binding sites in addition to the diffusion coefficient:

19. Wachsmuth,M.; Weidemann,T.; Muller,G.; Hoffmann-Rohrer,U.W.; Knoch,T.A.;
Waldeck,W.; Langowski,J. 2003. Analyzing intracellular binding and diffusion
with continuous fluorescence photobleaching. Biophys. J. 84:3353-3363.



-----Oorspronkelijk bericht-----
Van: Confocal Microscopy List [mailto:[log in to unmask]] Namens
Narasimham Jammi
Verzonden: woensdag 24 november 2004 0:59
Aan: [log in to unmask]
Onderwerp: FRAP experiments


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Hi all,
 I have a question regarding the number of bleach iterations one would want
to use in a typical FRAP experiment. I understand that one would want to
minimize the number of bleach iterations (preferrably limit it to 1 bleach
at 100% laser intensity) or else fall prey to the 'corona' effect at the
ROI, thereby leading to an increase (flawed) in the diffusion coffecients.
However, bleaching just once leads to uneven decrease in fluorescence
intensities over different samples (for eg, the intensity on ROI goes from
100% to 60% in sample 1, sample 2: 100% to70%, sample 3: 100% to 80% etc).
Does this make a difference in interpreting the data?

thanks
-Jammi