Description:

Podosomes are punctate actin-rich cytoskeletal structures used by dendritic cells and macrophages to sense the mechanical properties of the surrounding extracellular environment, helping them patrol for pathogens. Podosomes are sensitive to substrate stiffness and probe the extra-cellular matrix by polymerizing actin from the cap against the plasma membrane, exerting force onto the substrate and detecting the opposing forces. Cycles of polymerization and collapse result in height oscillations of the podosome core. Interestingly, podosomes form clusters in cells that exhibit collective oscillatory behavior, resulting in podosome height waves in which a local group of podosomes sequentially increase and then decrease their F-actin content. We have previously studied the oscillatory dynamics in podosomes using image correlation analysis of fluorescence microscopy image time series. Image correlation methods are an extension of fluorescence fluctuation spectroscopy that can measure protein-protein interactions and macromolecular transport properties from input fluorescence microscopy images of living cells. These approaches are based on space and time correlation analysis of fluctuations in fluorescence intensity within images recorded as a time series using a fluorescence or super-resolution microscope. I will introduce spatio-temporal image correlation spectroscopy (STICS) and its 2-color cross-correlation variant (STICCS) and describe the application of the image correlation methods for characterizing intensity waves of talin, vinculin as well as filamentous actin imaged via confocal and Airy scan super-resolution fluorescence microscopy for networks of assembling and disassembling podosomes in human dendritic immune cells. I will briefly introduce a new biophysical model that recapitulates the collective podosome dynamics and focus on the application of STICS on both simulated and experimentally measured podosome wave dynamics within cells under different treatment perturbations to validate the theoretical model.

Paul Wiseman, Professor, McGill University

Host: John Marko