High-resolution 3D refinement

At this point in the tutorial, we have obtained a refined map at binning factor 2, we have removed any duplicate particles, as well as any bad particles that do not align well with our map. We are now ready to perform 3D refinement at binning factor 1.

Pseudo-subtomograms and reference map at bin 1

First, we need to generate new pseudo-subtomograms and a reference map at binning factor 1. The order of running the Extract subtomos and Reconstruct particle jobtypes is irrelevant as long as they are run consecutively to keep track of the optimisation set file. In addition, since the previous job we ran was a Subset selection job, we must use its output particles file as the input particle set to the next job (either Extract subtomos or Reconstruct particle):

Input optimisation set::

“”

OR: use direct entries?:

Yes

Input particle set:

Select/job018/particles.star

Input tomgoram set:

Denoise/job008/tomograms.star

Input trajectory set:

“”

For 3D refinement at binning factor 1, make sure the following options are properly set on Extract subtomos Reconstruct tab and Reconstruct particle Average tab:

Binning factor::

1

Box size (binned pix)::

512

Cropped box size (binned pix)::

192

Masks for high-resolution refinement and FSC estimation

Next, we need to generate appropriate masks to help the refinement process and FSC assessment. In the particular case of the HIV capsid, we provide the following masks:

1. mask_align.mrc, which we will use in the Reference mask field of the 3D auto-refine job: Since the refined region in our structure so far contains both the HIV capsid and the matrix, we need to make sure that we only focus on the capsid. Moreover, this mask is nearly as wide as the 230Å diameter mask applied to the images during refinement, ensuring that we use as much of the information available in the volume as possible to align the particles.

2. msk_fsc.mrc, which we will use in the Solvent mask field of the Post-processing job (see Post-processing below). Since we use a wide mask to improve the alignment of particles during refinement, the volume we refine will consist of more than one hexamer. In order to asssess the reconstruction quality of the central hexamer only, we use a tighter mask around it for FSC calculations.

The above masks can be created externally using tools like UCSF chimera or dynamo_mask_GUI from the dynamo package. For general mask creation, refer to SPA tutorial mask description.

In order to use the provided masks, we suggest recentering the reference map to ensure that the masks and the reference are aligned (so that the masks focus on the capsid). You could look at the output reference map from the previous step (Reconstruct/job025/merged.mrc) and the mask (masks/mask_align.mrc) with a 3D viewer like IMOD 3dmod to estimate the Z offset between both maps, in pixels. In our case, it is 2.75 pixels but this could be different as it depends on the initial de novo model. Thus, recentering the particles can be done from the command-line:

relion_star_handler --i Extract/job020/particles.star \
--o Extract/job024/particles2.75.star --center --center_Z 2.75

To check that the capsid within the reference map is aligned with the mask, we can reconstruct it using the Reconstruct particle job-type, described in Reconstruct particle.

Running the auto-refine job at bin 1

On the I/O tab of the 3D auto-refine job-type set:

Input optimisation set::

Extract/job020/optimisation_set.star

OR: use direct entries::

No

(If a new particles file has been generated in the previous step during recentering, this option should be set to Yes and the correct input particle set and tomogram set files should be used.)

Reference map::

Reconstruct/job021/half1.mrc

(Once we reach a high enough resolution in the refinement process, it is important to keep the two halfsets entirely separate in order to obtain a gold-standard reconstruction. Halfmap files should be used as reference maps for each halfset processed by relion_refine, keeping the 3D refinement of both halfsets independent along the whole workflow. To that end, when the reference map file name contains either *half?*.mrc template, each halfmap is automatically assigned to its halfset.)

Reference mask (optional)::

mask_align.mrc

On the Reference tab, set:

Ref. map is on absolute greyscale?:

Yes

Resize reference if needed?:

Yes

Initial low-pass filter (A):

5.5

(We set the low-pass filter slightly below the reached resolution in the previous step. In this case, it’s Nyquist resolution at binning factor 2.)

Symmetry:

C6

On the CTF tab set:

Do CTF correction?:

Yes

Ignore CTFs until first peak?:

No

On the Optimisation tab set:

Mask diameter (A)::

230

Mask individual particles with zeros?:

Yes

Use solvent-flattened FSCs?:

Yes

(This option enables the computation of the resolution during refinement using masked halfmaps using the provided mask_align.mrc mask file.)

Use Blush regularisation?:

No

On the Auto-sampling tab set:

Initial angular sampling::

1.8 degrees

On our system, using 2 GPU cards, this job took around 1.5 hours to run.

We now remove duplicates again by running Subset selection with a minimum inter-particle distance of 50Å to ensure that no other particles converged to the same positions, and then generate a new reference map with Reconstruct particle.

Post-processing

Finally, the procedure to sharpen a 3D reference map and estimate the gold-standard FSC curves for subtomogram averaging is the same as described in the SPA tutorial.

Select the Post-processing jobtype, and on the I/O tab, set:

One of the 2 unfiltered half-maps::

Reconstruct/job025/half1.mrc

Solvent mask::

mask_fsc.mrc

(This is the tight mask that only includes the central hexamer.)

We leave the other fields as they are and run the job. The resulting final resolution we see in our workspace is 4Å.

At this point, this is the best alignment we could reach without applying any specific tomo refinement, as shown in the Tomo refinement cycle section.