Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Cells can crawl, self-heal, and tune their stiffness due to remarkably dynamic cytoskeleton. As such, reconstituting networks of cytoskeletal biopolymers may lead a host active adaptable materials. However, engineering such materials with precisely tuned properties requires measuring how the dynamics depend on network composition synthesis methods. Quantifying is challenged by variations across time, space, formulation space composite networks. The protocol here describes Fourier analysis technique, differential microscopy (DDM), quantify biopolymer particularly well suited for studies cytoskeleton DDM works time sequences images acquired using range modalities, including laser-scanning confocal, widefield fluorescence, brightfield imaging. From image sequences, one extract characteristic decorrelation times density fluctuations span wave vectors. A user-friendly, open-source Python package perform also developed. With this package, measure labeled components or embedded tracer particles, as demonstrated data intermediate filament (vimentin) actin-microtubule Users no prior programming processing experience will be able software associated documentation.