Cryogenic electron tomography (cryo-ET) is a powerful method to study protein structures and macromolecular complexes. These studies can provide structural information at the nanometer scale, allowing for the visualization of ultrastructures and access to sub-nanometer information through subtomogram averaging of localized particles (STA). STA alignments can provide analysts with an opportunity to quantify relationships between particles; however, the analytical tools to accomplish this are often lab or system specific. We offer an adaptable script package, tomoPoseLink, that can be applied to systems with polymer assembly and ultrastructures in a definable region of interest. We introduce a modular MATLAB script package for a bottom-up, unbiased analysis of head-to-tail polymerization in subtomogram averaging (STA) datasets, based on analyzing the positions and orientations of neighboring particles. Our approach requires no prior segmentation, knowledge of interactions, or reference structures, and runs quickly on CPUs due to its reliance on numerical rather than image classification. The numerical classification also allows estimation of error rates and provides the user greater control over accuracy and sensitivity in identifying bound conformations. Analyses include occupied volume, protein concentration, classification into bound/unbound, and fibril bundling, and the modular nature of the package facilitates adaptation for other purposes. We demonstrate the protein binding analysis using a model system of Rubisco in α-carboxysomes (α-CBs), showcasing the toolkit’s ability to evaluate global data such as volume and global organization, polymerization data such as twist and bend, and lattice data such as lateral fibril distances and angles. These results present a method for a bottom-up approach to analyzing polymerization, where individual subunits are independently identified and their polymerization state is defined based on their coordinates and parameters within a region of interest. TomoPoseLink offers analysts a toolkit to conduct an adaptable biophysical analysis on STA data in an unbiased manner. The information generated will provide new insights into protein-protein interactions and the conditions favorable for the assembly and stability of larger ultrastructures. Particles can also be classified by polymer states for further STA processing. This script package can be used for scientists studying protein interactions within isolated compartments or other regions of interest appropriate for the biological system.
Aguilar et al. (Sun,) studied this question.