Imaging Fluorescence Cross-Correlation Spectroscopy as a Tool to Study Cell-Membrane Organization

Abstract

The structure of biological membranes has been investigated for many years. However, progress is hindered by the fact that putative domains are highly dynamic and their size is smaller than the optical diffraction limit and thus direct observations are difficult. Therefore, there is a need to develop new biophysical tools which can infer the existence of domains within membranes and can follow their development over time. We have introduced in the past a method called Imaging Total Internal Reflection-Fluorescence Correlation Spectroscopy (ITIR-FCS) using EMCCD or sCMOS cameras. ITIR-FCS allows the measurement of a large number (up to ∼0.5 million) correlation curves at contiguous locations on cell membranes of live cells with millisecond time resolution. The spatial information within the data can be used to obtain information on the structure and organization of the membranes. This is achieved by calculating differences between the forward and backward cross-correlations between adjacent pixels A and B (CCFAB - CCFBA) or A, B, and C (CCFAB - CCFCB). The results can be depicted as histograms referred to as ΔCCF distributions. In this work we conduct measurements on supported lipid bilayers and cell membranes and perform simulations to demonstrate how ΔCCF distributions change characteristically with membrane complexity and structure. In particular, we demonstrate that domains with sizes below the diffraction limit have a characteristic broadening effect on the ΔCCF distributions. As an example we show that changes in membrane structure and organization of live neuroblastoma cells can be followed over the time course of an hour or more by way of ΔCCF distributions. To deal with large amount of data collected we developed an open source software, ImFCS, to calculate and fit the auto- and cross-correlation functions and depict the results in an imaging format.