One method to evaluate proteins under native conditions is Fast Relaxation Imaging (FReI) microscopy, where fluorescence changes from FRET labeled proteins report on the protein structure providing thermodynamic and kinetic information on protein folding. One advantage to this technique is the spatial information available; but the large number of pixels, frames, and associated thermal perturbations form a high dimensional data set. Since the cellular microenvironment is highly heterogenous and dependent on organelle and location in the cytoplasm, it is important to be able to separate unique protein structures and dynamics across the cell. However often FRET values are averaged over the cell area, with some analysis done on either individual pixels or presupposed regions. Our work into uses convolutional similarity metrics to allow for spectral cluster of time resolved time-resolved microscope images to distinct regions based on small differences in fluorescent changes over time. In protein and RNA folding systems, separations with these methods have for resolution of distinct cellular regions with different kinetic and thermodynamic properties. Since the method is purely data driven it can be used to study many localized processes in or across cells, such as how structural differences induced by the microenvironment surrounding proteins confer function in relation to the protein’s location within a cell.

Spectral clustering analysis of microscopy videos for study of localized cellular processes

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ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.