A nu-space for image correlation spectroscopy: characterization and application to measure protein transport in live cells

Abstract

We introduce a new generalized theoretical framework for image correlation spectroscopy (ICS). Using this framework, we extend the ICS method in time–frequency ( ν , nu) space to map molecular flow of fluorescently tagged proteins in individual living cells. Even in the presence of a dominant immobile population of fluorescent molecules, nu-space ICS (nICS) provides an unbiased velocity measurement, as well as the diffusion coefficient of the flow, without requiring filtering. We also develop and characterize a tunable frequency-filter for spatio-temporal ICS (STICS) that allows quantification of the density, the diffusion coefficient and the velocity of biased diffusion. We show that the techniques are accurate over a wide range of parameter space in computer simulation. We then characterize the retrograde flow of adhesion proteins ( α 6- and α L β 2-GFP integrins and mCherry-paxillin) in CHO.B2 cells plated on laminin and intercellular adhesion molecule 1 (ICAM-1) ligands respectively. STICS with a tunable frequency filter, in conjunction with nICS, measures two new transport parameters, the density and transport bias coefficient (a measure of the diffusive character of a flow/biased diffusion), showing that molecular flow in this cell system has a significant diffusive component. Our results suggest that the integrin–ligand interaction, along with the internal myosin-motor generated force, varies for different integrin–ligand pairs, consistent with previous results.