Sub-tomogram averaging

The following was written by Tanmay Bharat.

Getting organised

As in single-particle projects, also sub-tomogram averaging is organized in a single ProjectDirectory for each structure/project (also see the recommended procedures). Inside this directory it is recommended to make a Tomograms directory. Inside this directory, one should make a separate directories for each of the recorded tomograms (e.g. Tomograms/tomo0001). (Optionally, the Tomograms directory may contain sub-directories to group sets of tomograms, becase for example they were collected on different days (e.g. Tomograms/12Mar2015/tomo0001). You are free to choose whatever names for your directories and your tomograms. We have only used IMOD for tomogram reconstruction, but there is no reason why other software packages could not be used. The important thing is to save the tomogram in MRC format, and with a .mrc extension. In each of the individual tomogram directories you will need 4 files:

tomo.mrc    : the actual reconstructed tomogram
tomo.st     : the aligned tilt series in MRC format (e.g. save this from IMOD) 
tomo.coords : a text file with 3 columns: the X, Y and Z coordinates of the subtomograms (e.g. save this from IMOD)
tomo.order  : a text file with 2 columns: the tilt angle of each image in tomo.st and the accumulated dose in electron/A2 for that image.

You are free to change the rootname of these files (in this case "tomo"), but the extensions have to be like the ones above.

Generating STAR files and script for CTF-reconstructions

Tanmay Bharat wrote the relion_prepare_subtomograms.py script to run CTFFIND on all images of the tilt series stack (please note that an extension of this script to include CTF-estimation from two neighbouring exposure areas is still pending). This script also generates the input particles.star file for sub-tomogram refinement, and the STAR files that are required for the reconstruction of the 3D CTF models for each subtomogram. In addition, this script generates a shell script (called tomo_reconstruct_ctfs.sh) inside the directory for each tomogram. with all relion_reconstruct commands to reconstruct the 3D CTF models for all subtomograms in the next step. Note that this script depends on python, IMOD, RELION and CTFFIND (version 3 or 4). It alsoThe input for the bla.py script is a RELION-type STAR file with one line for each tomogram. It looks like this:

data_
loop_
_rlnMicrographName
Tomograms/tomo001/tomo.mrc
Tomograms/tomo002/tomo.mrc
Tomograms/tomo003/tomo.mrc

One way to make it would be:

relion_star_loopheader rlnMicrographName > all_tomograms.star
ls Tomograms/tomo???/*.mrc >>  all_tomograms.star

After making this STAR file, edit the header of the bla.py script to provide information about the experimental setup and execute it using:

python bla.py

Generating 3D CTF models for sub-tomogram averaging

The previous script generates a shell script called bla, which needs to be executed from the command line to perform the reconstructions for the 3D CTF models of all subtomograms. You may parallelise its execution as is most suited for your computer setup.

• First CTFFIND should be run for all images of the tilt series (that was used to generate the tomogram). The results should be written out in a text file with the syntax:

Tilt_angle average_defocus_value_from_CTFFIND

This can be done automatically using the script run_ctffind.py. Please modify the header values of the script.

• Now the coordinates from the text file and the average defocus values from CTFFIND will be used to calculate local CTF parameters for each sub-tomogram in each image of the tilt series. This can be done using the

script make_ctfstar.py. Please modify the header values in this python script. For each subtomogram, a RELION .star file will be written out. This will be used by relion_reconstruct to generate the 3D CTF volume.

• Run relion_reconstruct to generate all 3D CTF model volumes. This can be done using the script reconstruct_CTF_volumes.sh that was written out in the last step. This script uses the .star file to read the local CTF

parameters and use them to make the 3D CTF model volume.

Sub-tomogram extraction

• Extract sub-tomograms using RELION as you would do for 2D micrographs. If the image file is a volume and the coordinates values contain X,Y,Z entries, automatically sub-tomograms will be written out rather than 2D particles. If you add --project3d to the RELION extraction command, then 2D projections of each sub-tomogram will be written out. This may be useful to run reference-free 2D-class averaging in order to identify junk or otherwise unsuitable particles in your data set.

• Run 3D Auto-Refine or 3D classification jobs, just like you would for single-particles, but specifying the CTF volume for each image in a .star file (using the label "rlnCtfImage"). This can be done using the script prepare_subtomo.py. A sample output is shown in the script.

• All analyse results options (e.g. post-processing) stay the same as for single-particles.