Context-Aware Template Matching for Structural Analysis of Membrane-Assembled Retromer Coats

Cryo-electron tomography (cryo-ET) enables three-dimensional visualization of macromolecular complexes in near-native conditions, but analyzing these datasets remains challenging due to structural heterogeneity and the complexity of the sample context. I will present context-aware template matching, an approach that leverages sample features, such as membranes and supporting geometries, to improve particle identification. I will illustrate this method using retromer-coated membrane tubules, showing how template matching, in conjunction with subtomogram averaging, neighborhood analysis, and heterogeneity analysis, can reveal distinct classes of arch arrangements and global coating patterns. This example demonstrates how incorporating contextual information can enhance structural interpretation, providing a framework for studying complex membrane-associated assemblies in cryo-ET datasets.