Biology Reference
In-Depth Information
bundling because bundles exhibit brighter fl uorescence) in the
microfi lament-containing pixels using the macro: hig_skew-
ness.txt (Plugins > hig skewness).
3.5 Evaluating Actin
Bundle Thickness
Using the
Histogram Method
1. From original stack of optical sections obtained by CLSM,
prepare a maximum intensity projection (Image > Stacks >
Zproject) and save it as an 8 bits *.tif image (Image > type > 8bits).
2. Defi ne a specifi c line length by ROI selection
(Plugins > ROI > SpecifyLine); put the line across a representa-
tive area of the image (across a well-focused part of a cell;
see
Note 11
).
3. Generate a profi le of GFP fl uorescence intensity (Analyze > Plot
profi le) and record the brightness values of all peaks corre-
sponding to microfi lament bundles crossed by the line (values
appear on mouse over or generate a list of values by pressing
“List”). Record also background values in an area devoid of
actin fi laments.
4. Using the table calculator, subtract the average background
value from the peak values and generate a histogram of the
distribution of the resulting net peak values into three or four
equally broad classes of gray level (in arbitrary units). The
resulting plot documents microfi lament bundling, as low
intensity represents weakly labeled bundles or single fi laments
and high intensity corresponds to brightly labeled bundles.
3.6 Quantifying
Filament Dynamics
from VAEM
Image Series
1. Acquire temporal series of single-plane optical sections (XYT)
of the cortical cytoplasm of a cell expressing a suitable marker
by VAEM. We aim towards imaging at least fi ve plants per
sample, with 15-20 movies per sample evaluated (
see
Note 9
).
2. To measure microfi lament dynamics, select randomly ten actin
bundles per sample and measure their pause duration (for
monitoring over time, use multipoint selection tool in ImageJ
and register manually the time when the fi lament end shows a
change in behavior). Values and distribution of pause duration
can serve, e.g., as an indicator of differences either in bundle
size or in the degree of actin cross-linking ([
25
];
see
Note 12
).
3. To quantify microtubule turnover, select randomly 10-20
microtubule ends per sample and monitor their behavior over
time (2 min); use the pen or brush tool in ImageJ to mark the
already evaluated ends. Count microtubules in the four dis-
tinct phases (growing, shrinking, pausing, and alternating
between growth and shrinkage).
4. To estimate of microtubule growth and shrinkage rates, select
randomly 5-10 microtubule ends per cell and measure their
distances from the starting position during specifi c time using
ImageJ.
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