A feature-guided, focused 3D signal permutation method for subtomogram averaging.

ABSTRACT: Advances in electron microscope instrumentation, cryo-electron tomography data collection, and subtomogram averaging have allowed for the in-situ visualization of molecules and their complexes in their native environment. Current data processing pipelines commonly extract subtomograms as a cubic subvolume with the key assumption that the selected object of interest is discrete from its surroundings. However, in instances when the object is in its native environment, surrounding densities may negatively affect the subsequent alignment and refinement processes, leading to loss of information due to misalignment. For example, the strong densities from surrounding membranes may dominate the alignment process for membrane proteins. Here, we developed methods for feature-guided subtomogram align

SUBMITTER: Peters JJ 

PROVIDER: S-EPMC9149098 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature