Quantitative Mapping of Intranuclear Diffusion in Living Cells by Phasor Analysis of Local RICS

Abstract

Image Correlation Spectroscopy (ICS) (Wiseman, Cold Spring Harb. Protoc. 2015) based techniques are quantitative tools for assessing the concentration and dynamics of proteins diffusing in living cells. A wide variety of these methods (ICS, ICCS, RICS, kICS etc.) is applicable to commercial laser scanning microscopes in order to investigate subcellular biophysical properties, for instance the study of protein mobility within the nucleus of eukaryotic cells. Although powerful, these techniques may fail to retrieve a correct value when analyzing inhomogeneous samples, given that no further assumption is made on the specific nature of the inhomogeneity. Being the cell an intrinsically heterogeneous system, a prescreening method for the characterization of the heterogeneity of the system will increase the reliability of ICS techniques for cellular applications.In this respect, we recently introduced a method, based on the phasor analysis of local ICS (PLICS), for extending ICS to heterogeneous systems without the need of a priori assumptions (Scipioni et al., Biophys. J. 2016). The phasor approach, originally developed for the identification of components in fluorescence-lifetime imaging (Digman et al., Biophys. J. 2008), is used within the PLICS algorithm for the analysis of local spatial correlation functions as a fast and unbiased alternative to the fitting procedure. Here we present application of the PLICS concept to Raster Image Correlation Spectroscopy (RICS) (Digman et al., Biophys. J. 2005) for obtaining a map of intra-nuclear diffusion of expressed EGFP in living HeLa cells. The PLICS approach is used to provide a segmentation of the image into sub-regions with homogeneous diffusion coefficient, that is successively quantified by applying Arbitrary Regions Image Correlation Spectroscopy (ARICS) (Hendrix et al., Biophys. J. 2016),a state of the art technique developed for extending the ICS analysis to non-rectangular regions.We believe that PLICS could become a widely used prescreening approach, applicable to several kinds of ICS techniques, for addressing the heterogeneity of a dataset prior to the application of the technique. Furthermore, if the statistics is significant, PLICS is capable of providing an exhaustive mapping over the entire dataset of the property we are willing to measure.