Symmetric Particles in Subtomogram Averaging (new pipeline)

Symmetric biomolecules really aren't (symmetric). At some limiting resolution, the symmetry will always be broken. Consider 3 examples:

In canonical single particle reconstruction, you would simply impose the specified symmetry and hope for the best. Clearly, however, the structure resulting from a symmetrized average of non-identical or mispositioned components will not result in the best possible subunit resolution. We instead need a strategy to look at a single subunit at a time, and refine that, characterizing/classifying not entire symmetric particles, but on an individual subunit basis.

EMAN2 has 2 primary methods to permit this in the new subtomogram averaging pipeline (using e2spt_refine_new and related programs):

Approach 1 - re-extract particles centered on each oriented subunit

In this approach you begin with a normal symmetry-imposed refinement. Then, when you've done the best you can with the normal refinement, you use the resulting per-particle orientations to extract a new set of particles for each of the N subunits. ie - if you have N C4 particles, you will produce 4N smaller particles with no symmetry, and known initial orientations. These orientations could then be further refined or the 4N particles could be classified to produce self-similar subsets.

  1. Run a normal refinement following the tutorial. Be sure to use e2spt_refine_new when presented with the option of the older programs.

  2. The refinement will produce aliptcls3d_XX.lst and aliptcls2d_XX.lst files containing the particles with per-particle alignment data. The 3-D alignments are required for extraction of particles from the original tilt series.

  3. Re-extract the particles using one of these files, but impose symmetry and optionally recenter on a subunit. For example, if we wish to re-extract the raw tilt series with each particle copied 8 times (C8 symmetry) with the appropriate transformation on each particle:

e2spt_extract.py --boxsz_unbin=320 --label=particles_00 --newlabel=reextract --threads=24 --padtwod=2.0 --alltomograms --tltkeep=1.0 --jsonali spt_01/aliptcls3d_04.lst --postxf=c8,0,0,0

  1. However, the above command will keep the particles at their original size (320x320 pixels), including the density for the full particle in each subtilt. Normally you might prefer to re-extract a smaller box size with each of the 8 asymmetric units centered in the box. To accomplish this, we reduce boxsz_unbin and include a 3D translation in the --postxf option. The translation should be from the center of the box to where you wish the center of one subunit to be in the re-extracted particles. Each of the (in this case) 8 copies will be rotated to the position of the target subunit, then the smaller box will be centered on that point. The translation is specified as tx,ty,tz after the symmetry in --postxf, and --boxsz_unbin has been reduced:

e2spt_extract.py --boxsz_unbin=160 --label=particles_00 --newlabel=post40-mono2 --threads=24 --padtwod=2.0 --alltomograms --shrink=2.0 --tltkeep=1.0 --jsonali spt_40/aliptcls3d_01.lst --compressbits=8 --postxf=c8,72,0,0

  1. When you run a refinement on the extracted smaller box-size, make sure to provide an appropriate initial model with the same translation and box size reduction as used above. Note that no "subtraction" is done to eliminate the adjacent subunits in the extracted particles. So using a --maskalign in your subsequent e2spt_refine_new runs is a good idea. The mask.cylinder processor can be quite useful in generating suitable alignment masks for C and D symmetric objects. It is a good idea to give the mask a soft edge either by low pass filtering it (Gaussian blur) or using the tri parameters in mask.cylinder. e2filtertool.py is a very useful tool when fine tuning the parameters of such masks.

Approach 2 - replicate each particle N times and align with a mask

In this somewhat similar approach, rather than re-extracting particles, which can be a time consuming process, we simply make a modified .lst file "virtually" replicating each particle N times, without any actual changes to the data itself, then the refinement makes use of an alignment mask to focus the alignment only on a single subunit. This approach has the advantage of retaining the context of the complete assembly for each particle, with the region inside the mask having improved resolution. These results can then be subjected to, for example, e2gmm analysis to examine the dynamics of the overall assembly from the perspective of a single fixed subunit "anchor". The only disadvantage of this approach is the particles retain their full size, so for CN symmetry, the refinements will take N times longer since there are N times as many particles, and the box size didn't shrink. With Approach 1, if you reduce the box size by 2x, refinements will run ~10x faster due to the box size reduction but N times slower due to the replication. However, you lose the context of the full assembly.

  1. Run a normal refinement following the tutorial. Be sure to use e2spt_refine_new when presented with the option of the older programs.

  2. The refinement will produce aliptcls3d_XX.lst and aliptcls2d_XX.lst files containing the particles with per-particle alignment data. The 3-D alignments are required for extraction of particles from the original tilt series.

  3. Copy the last iteration aliptcls3d_XX.lst to sets/ with an appropriate name, for example:

cp spt_01/aliptcls3d_04.lst sets/spt01_04_c8.lst

  1. Use e2proclst.py to symmetrically replicate each subtilt, for example:

e2proclst.py sets/spt01_04_c8.lst --sym c8

  1. Note that this command operates in-place on the .lst file, replicating the particles in the same file, so you should not run it on the original file in the spt_XX folder, or the results in that folder won't be valid any more, and you should never run the command twice on the same file (or you will end up with N^2 copies).
  2. Make a mask for a single subunit from the previous refinement results.
    • The mask.cylinder processor can be quite useful in generating suitable alignment masks for C and D symmetric objects. It is a good idea to give the mask a soft edge either by low pass filtering it (Gaussian blur) or using the tri parameters in mask.cylinder. e2filtertool.py is a very useful tool when fine tuning the parameters of such masks.

    • Alternatively, you can do something like use the segger module in Chimera to extract a single subunit from the volume, then use a sequence of filter.lowpass.gauss and threshold.binary operations to turn the extracted subunit into an appropriate subunit mask which more closely follows the shape of the actual assembly. If you do this, make sure that the mask is at least 10-20 Å larger than the surface of the subunit, and has a soft edge.

    • When making alignment masks it is always critical that the edge of the mask have a "soft" Gaussian edge, with a with of at least 1.5 - 2x the target resolution. For example, if you are targeting 4 Å resolution, a binary mask should be lowpass filtered to at least 8 Å before using it for alignment.


note about "subtraction" methods - In the mid 2000s, EMAN2 offered an experimental approach for single particle analysis (which still exists) for not just masking out the individual subunits from symmetric particles, but subtracting away the density for the other subunits. That is, if you had a C4 particle, when extracting a subunit, you would subtract away the density for 3 of the 4 subunits, ostensibly leaving behind only the density for the subunit you wish to consider. This idea later propagated into Relion where it is considered a standard method there. However, there is a logical flaw of sorts in this scheme. If the macromolecule was perfectly C4 symmetric, it would, indeed, be possible to subtract away the other subunits. However, in that case, there would be no reason to do so, since a C4 refinement would yield optimal results. If the symmetry is broken then any subtraction we do will leave behind artifacts wherever the symmetry is broken, and, indeed, these artifacts are the only thing which should interfere with the correct alignment of the particle in the first place, so in the end, subtraction doesn't really accomplish anything very useful, with some minor caveats.

EMAN2/TomoSymmetry (last edited 2023-04-06 12:58:53 by SteveLudtke)