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RCT OTR overall workflow

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Michael A. Cianfrocco edited this page Jun 9, 2018 · 7 revisions

Home > RCT OTR overall workflow

Why do we have to calculate ab initio models for new macromolecular samples?

Single particle EM requires an initial 3D model in order to begin 3D analysis

Due to the fact that the single particle images are noisy 2D projections from a 3D object (or multiple 3D objects), all 3D analysis requires an initial model to start with. If you know the 3D structure of your sample, then you can use that 3D model as an initial model, BUT, if you are studying a new sample, you will need to calculate the 3D initial model from scratch.

In order to calculate a new 3D model, you will take advantage of particle tilt mates in the electron microscope. By collecting images at known tilt angles, you can combine thousands of particles from these known tilt angles to perform a rough 3D reconstruction using Random Conical Tilt (RCT) or Orthogonal Tilt Reconstruction (OTR). To read more about these methods, see this review here.

Guide for RCT/OTR 3D model calculation

  1. Collecting tilt pairs
  • For good quality 3D RCT/OTR volumes, you will need at least 2,000-6,000 particle tilt pairs
  • You will want to collect the tilted image at the highest tilt allowed by your stage. This typically ends up being 45 degrees and higher.
  1. Picking particles
  1. Estimating CTF & tilt angle of tilted micrographs
  • The tilt axis & tilt angle of the tilted micrograph is required for performing the 3D reconstruction using the tilted particles.
  1. Extracting tilt mate particle stacks
  • Particles must be extracted from the untilted and tilted micrographs in such a way as to make sure that there are two stacks: 1) untilted particle stack and 2) tilted particle stack. AND, there is exact correspondence between the two stacks: particle #1 in the untilted stack must have its tilt mate as particle #1 in the tilted particle stack.
  1. Removing 'bad' particles from particle stacks
  • If you ended up picking 'junk' during the particle picking phase, you can use this approach to remove 'junk' from BOTH untilted and tilted particle stacks:
    • Classify the untilted stack over a single round of Auto_Align.py using the --oneIter option
    • Record a list of 'bad' class averages
    • Run remove_bad_classes.py on BOTH untilted and tilted stacks so that they stacks maintain the same registry, where untilted particle #1, position 1 is paired with tilt particle #1, position 1.
  1. 2D classification of untilted particle stack using Auto_Align.py
  • In order to perform RCT/OTR, you will need to classify & align the untilted particle stack using Auto_Align.py. Then, using the tilt mates for each class average (along with the tilt angle, previously calculated), you can calculate 3D models for each class average using the tilted particles.
  1. 3D reconstruction of individual 2D class averages for RCT/OTR
  • After running Auto_Align.py on the untilted particles, you can reconstruct the tilted particles using the information from 2D classification and the tilt angle.
  1. Filtering, thresholding, masking 3D models
  • With the RCT volumes, you can now begin 3D classification/refinement. But, considering the presence of a missing wedge in your 3D volume, it can help your 3D classification/refinement by masking away extraneous densities from the 3D model. This involves invoking a procedure like 'solvent flattening', where densities outside of a given distance from the 3D structure will be removed since we know they are not real protein density features.
  1. Refining RCT/OTR volumes against untilted particle dataset
  • Now that you have a filtered, masked RCT initial volume, you should perform 3D classification/refinement against a large untilted particle stack. This usually is a much bigger dataset than the untilted tilt mates for the tilted particles (> 20,000 particles) and will allow you to refine the 3D features observed in the initial volume.

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