Biology Reference
In-Depth Information
up and down (along the
z
-axis) to get the plasma membrane positioned in the center
of the observation volume. Monitor the counts per molecule while making small ad-
justments, in 0.1
m steps, along the
z
-axis. Find the position in
z
corresponding to
the maximal counts per molecule, and then make a 10 by 10 s FCS recording from
that position. Save the data file and move to a different region of the coverslip, select
a new cell, and begin again. Each time, adjust the sample focus along the z-axis to
find the optimal positioning of the membrane in the observation volume. Make re-
cordings from at least 5 to 10 different cells. Repeat the process for the tagged re-
ceptors of interest and end the session with another control sample. Repeat the
process with freshly prepared cells on two additional test days.
m
10.2.4
Data analysis
Commercially available systems can be purchased with autocorrelation analysis soft-
ware. If using a homebuilt system, software such as Origin or MATLAB can be used.
10.2.4.1
Diffusion coefficient
As the fluorescence-tagged receptors pass through the laser-illuminated observation
volume, the fluctuations in fluorescence intensity are recorded in real time by the
photon-counting detector, and a fluorescence intensity trace for the observation pe-
riod is generated (
Fig. 10.3
A). During the first two 10 s intervals of the 100 s FCS
recording time, photobleaching of the immobile fraction of plasma membrane recep-
tors occurs. For G-protein-coupled receptors, this typically represents 40-50% of the
receptor pool. Data analysis is performed on the mobile fraction of receptors mon-
itored in the third through tenth 10 s FCS recording intervals (runs 3-10). Autocor-
relation analysis of the fluorescence signal is performed as in Eq.
(10.5)
:
h
d
ðÞ
t
d
ð
t
þ
t
Þ
i
F
F
G
t
ðÞ¼
(10.5)
2
h
Ft
ðÞ
i
where
G
(t) is the
of the change in fluorescence fluctuation intensity
(d
F
) at some time point (
t
) and at a time interval later (
t
h
time average
i
t) divided by the square of
the average fluorescence intensity. Autocorrelation analysis of the fluorescence in-
tensity trace is performed using a nonlinear least-squares fitting routine that graph-
ically represents the autocorrelation function
G
(t) on the ordinate and diffusion time
on the abscissa (
Fig. 10.3
B).
The rate at which the fluorescence-tagged receptor diffuses within the plasma
membrane is reported as the average dwell time (t
D
) within the observation volume
and is calculated from the midpoint of the autocorrelation decay curve. For autocor-
relation analysis, select a 2Dmodel for plasma membrane receptors or a 3Dmodel for
cytosolic receptors. Most autocorrelation curves will have a minimum of two com-
ponents, a very fast component (
þ
1 ms) related to the photophysical properties of the
fluorescent probe, and a slower component representing the diffusion of the
fluorescence-tagged receptor. Begin by fitting the data to a two-component model.
The examples shown in
Fig. 10.3
B are best fit by a two-component, 2D model with
<
