Cryo-ET Processing Pipeline
The tomography counterpart to our single-particle workflow: taking cells from raw tilt series to subtomogram averages that reveal macromolecular organization in its native context. Adapted from the SBGrid NIH R25 Train-the-Trainer CryoET curriculum, co-led by our lab.
Workflow steps
A complete tomography workflow from raw tilt-series data through subtomogram averaging and presentation of results — the same sequence taught in SBGrid's two-day CryoET Data Processing curriculum.
Cryo-ET workflow overview
Review the full tomography pipeline and project organization before processing, since cryo-ET workflows combine several specialized tools in sequence.
Denoising & missing-wedge correction
Apply denoising to improve contrast and use missing-wedge correction or restoration to reduce reconstruction artifacts from limited tilt range.
Segmentation & particle identification
Segment cellular features of interest (e.g. membranes, organelles) and identify candidate particles for further averaging.
Particle export
Export particle coordinates and sub-volumes from the tomogram for downstream subtomogram averaging.
Figure generation & presentation
Generate segmentation renderings and averaged-structure figures, and prepare final results for presentation — mirroring each workshop's final participant presentations.
Worked training example
Milled Saccharomyces cerevisiae cells — SBGrid Data Bank 1255
The SBGrid CryoET Train-the-Trainer curriculum runs this pipeline on a public training dataset of tilt-series from milled Saccharomyces cerevisiae cells, made available through the SBGrid Data Bank (doi:10.15785/sbgrid/1255) by the Raunser Laboratory, Max Planck Institute of Molecular Physiology. The dataset shows mitochondria, nuclear envelopes, lipid bodies, smooth endoplasmic reticulum, and other intracellular components — roughly 37 GB of authentic in-cell tomography data.
References
Primary sources for this workflow. Each link goes to the original resource so you can confirm details directly.