Tomography processing notes

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This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

See also EM software notes

On gold fiducials

Apparently in theory there's

  • Au11 (0.8mn) a.k.a. undecagold,
  • Au25 (0.9mn),
  • Au38 (1.1nm),
  • Au68 (1.3nm),
  • 1.4nm, often referred to as nanogold,
  • Au102 (1.5nm),
  • 1.8nm, a.k.a. Ni-NTA–Nanogold(verify)),
  • Au114 (2.0nm)
  • Much larger is colloidal[1] (so sizes are a little more approximate), often one of
    • 5nm
    • 10nm
    • 15nm
    • 20nm
    • 25nm

Apparently most commonly it's 5nm or 10nm, sometimes nanogold(verify).

See also "[Site-specific biomolecule labeling with gold clusters." (PMC3568671)


IMOD

The overall steps in reconstruction


A typical approach is described in imod. See e.g.

the overall diagram in "Automated tilt series alignment and tomographic reconstruction in IMOD"
See also "Tomography Guide for IMOD Version 4.9"
and a list of parts (some optional) in the batchruntomo man page.
and its tutorial https://bio3d.colorado.edu/imod/doc/batchExample.html


  • remove X-rays, pixel defects
  • removing dark/blank images
  • Rough correlation - basically, minimize it jumping about, otherwise not solving anything
    • e.g. cross-correlation
  • Finer alignment, by one of:
    • fiducial alignment (fiducials are small high-contrast things, typically gold beads)
    • fiducialless alignment, e.g. patch tracking
    • skipping (effectively assumes rough alignment is enough, which it basically never is)

Fiducial tracking can be done by manually telling it which correspond, or doing it via IMOD, or RAPTOR, or other.

Doing fine-detail alignment with fiducials is a nontrivial optimization problem. Using more makes for finer detail in the alignment (averages and noise), but also requires and kicking out the ones that seem to disagree with the consensus, because a few bad cases would throw off otherwise detailed averages.

  • combine aligned images into stack
  • correct CTF (optional)
only really required for higher resolution, which you may not need
  • remove fiducial markers from images
would be disturbing influence in tomogram
  • filtering
  • make tomogram from the stack
    • weighted backprojection (WBP), or SIRT (Simultaneous Iterative Reconstruction Technique)
  • cut out things that aren't specimen (optional, but rather practical)
  • noise reduction via NAD (nonlinear anisotropic diffusion) filter (optional)
  • where applicable: combine dual axis tomogram
  • Optional: Subvolume averaging (if you have multiple of the same thing within a tomogram that you want to combine (sort of single particle style)



Etomo

PEET (Particle Estimation for Electron Tomography) [2]

RAPTOR (Robust Alignment and Projection Estimation for Tomographic Reconstruction) used to be separate, and is now integrated, and a more automatic alternative. [3]



Automation:

  • batchruntomo is essentially a job manager
you give it directive files (adocs)


The list of directives: https://bio3d.colorado.edu/imod/doc/directives.html (you also have a directives.csv with similar content)

Directives are sorted into:

  • setupset - mostly describes collection and dataset
  • com-param - parameters for programs (like in .com files)
  • run-time - parameters interpreted by batchruntomo or etomo (verify)