Three Dimensional Reconstruction
of Ryanodine Receptor Using
Random Conical Tilt Pairs
These instructions allow to perform a two-dimensional analysis and to
create a 3D structure from images obtained on the electron microscope.
Tilt pairs are selected with
the command "particles" in web and windowed.
The zero-degrees images are subjected to 2D alignment
towards a reference.
Multivariate classification analysis is applied to
discern different
groups. At this point, either a 2D analysis
-including determination of the 2D resolution and
four-fold symmetrizing a 2D average- or
a 3D reconstruction can be performed. In the latter
case, the 3D is obtained using the rotational parameters and the tilt
single particles for a selected group. Procedures to determine the
resolution of a volume
and to four-fold symmetrize a volume are included.
updated 6/9/97, Montserrat Samso
written 5/20/97, Montserrat Samso
Two-Dimensional Alignement with Reference and Preparation of Tilted Images
1.Micrographs in the scanner format can be converted to Spider
format using (b01.cpf)
This creates files in spider format, one with original size and
another reduced (use an even number, e.g.4).
2.Choose command PARTICLES in Web and select pairs from the
reduced size micrographs. Do the
option Fit angles regularly, and check fitted positions.
Choose 10-15 windows in representative areas where there are no particles, using
option Background.
3.Window images out from tilted (b01.twi)
and untilted (b01.uwi)
micrographs. This will create a continuous image series and correct for the
different background in particles from different micrographs. A
rotation equivalent to the phi angle is performed. The header of
each image contains the tilt angle.
4.Create a selection file for the whole image series.
b02.sel
5.Centration of particles by cross-correlation with reference.
The reference
can be a blob or a circularly symmetrized and low pass filtered
version of an existing 2D average of the particle. Edit
rcucent.ori
to either create a blob or call an external reference.
b01.ori
Run it with oldspider.
6.First round of orientational alignment towards a given reference.
a. Mask and low pass a good average of hte sample interactively using
@rcal1pre to create the reference.
Run it with oldspider.
b. b02.ori.
This batch file calls the procedure
@rcal1h
Run it with oldspider.
7.Get aligned untilted and tilted images.
Second and third round of orientational alignment using average of first
alignment as a reference; sum of all rotation and shift
parameters, centration of the tilted images respect their 0 deg
pairs, get individual rotational angle on the headers.
a. Create average of resulting oriented images using spider command AS
b. Mask and low pass obtained average interactively using @rcal1pre.
Run it with oldspider.
c. b03.ori.
Run it with oldspider.
This batch file calls the following procedures:
rcal1h
sumcddd
rcsumshh
rclabel2mod
rctcenh
5-7.If there is an existing reference for this set of particles (e.g.
we are adding more particles to the dataset),
steps 5-7 can be done at once as we already have the averages, using the batch file
b04.ori
The only precaution is that there has to be the first
image of every series, as the procedure use it to know the file
dimensions.
Run it with oldspider.
8.Check that the final aligned images are correct (e.g.,
displaying the averages and variances):
b05.ori
and delete all intermediate files.
9.Remove unaligned particles and junk, and copy the good (aligned) ones to
another directory in a continuous file series.
a.In WEB use the Categorize command by
displaying the image files and manually clicking on each bad particle
under category 2 and saving the file numbers into a document file. It
is better to repeat the same process for the tilted images and saving the
file numbers in the same document.
b.In spider, run operation AT IT to put the particle
numbers in a consecutive order. Check the total number of bad
particles.
c. Run b06.sel
Go to the next step (classification).
Multivariate Classification Analysis of the 0 Degree Images
10.Low pass filter the 0 deg projections.
b85.fqu
11.Create a mask.
BC of a final average low pass box 10,10, filtration 0.5
FS and get average value
TH M above average value
BC of the resulting mask
FS and get average value
TH M below average value
12.First part of CORAN. This file has to be run in the
directory where we want the IMG file.
b01.cas
13.Second part of CORAN. This file has to be run in the directory
where the IMG file is.
b03.cas
14.Check the first 8 factors (specially clockwise/anticlockwise) with
the procedure
evalcoran,
b01.eva
15.Get different groups of particles.
a.In web, use command Dendrogram and check a good threshold to
differentiate between clockwise and anticlockwise projections.
b.Run CL HE to create selection files.
c.If it's necessary to join 2 groups but excluding some other
and it's not possible doing it by CL HE, join the selection
files by editing them. Use a batch file to add a constant to
the key number.
b03.sel
d.Run AS DC to get averages for every group.
e.Run AS R to get averages that can be used in the t-test,
useful when two-dimensional averages are compared.
16.Create 2 parallel directories for clockwise/anticlockwise
particles.
b05.sel
At this point either Two-dimensional analysis
or Three Dimensional Reconstruction can be
performed.
Two-dimensional Analysis
17.Get the resolution for every average.
b03.rf2.
18.Four fold symmetrize averages using the procedure
rav2dal,
b01.4fo.
19.Comparison of two samples with the same overall conformation
which differ in a certain area, using
DR DIFF.
a.Obtain reference using @rcal1pre.
b.Orient the four-fold symmetrized images.
b14.ori.
c.Create a mask as described in point 11.
d.Normalize images.
b01.cor.
e.Stack 3 images in order to make a volume, and perform DR DIFF.
This operation works only with volumes.
b01.stk.
f.Pick a slice of the volume containing the difference PS Z.
g.Four fold symmetrize.
b01.4fo.
h.Threshold this slice to select positive differences. TH M.
Use the option "below". A good value to start is the average
value of the image.
3D Reconstruction Using Weighted Back Projection Algorithms
20.Remove unaligned particles and junk, and copy the good (aligned) ones to
another directory in a continuous file series.
a.In WEB use the Categorize command by
displaying the image files and manually clicking on each bad particle
under category 2 and saving the file numbers into a document file. It
is better to repeat the same process for the tilted images and saving the
file numbers in the same document.
b.In spider, run operation AT IT to put the particle
numbers in a consecutive order. Check the total number of bad
particles.
c. Run b06.sel
21.Create 2 parallel directories for clockwise/anticlockwise
particles.
Create a selection file for each (clockwise/anticlockwise)
series.
b02.sel
Copy particles to each directory using a continuous series and
perform 3 rounds of BP XY and
altovol
using batch file b01.rec.
Run it with oldspider.
22.Calculate total shift and compute 3D using back projection
algorithms.
b02.rec
Run it with oldspider.
23.Take a quick look at the reconstruction (low pass filter, invert
sign).
b03.rec.
24.Four fold symmetrize volume. This batchfile calls the procedures
rav3dal
cmask3d3
b04.rec
Run it with oldspider.
25.Split select file used in 3D into two separate select files to be
used in the following two 3D reconstructions for comparative
purposes.
b05.rec
26.Compute two 3D reconstructions of the odd and even particles for clockwise set.
b06.rec
27.Compute two 3D reconstructions of the odd and even particles for anticlockwise set.
b07.rec
28.Compare the two half volumes
b08.rec
29.Use gnuplot to view the resulting curve
Plot 'rfdoc' using 3:5 with lines