ABSTRACT
Co-localization analysis is a widely used tool to seek evidence for functional interactions between molecules in different color channels in microscopic images. Here we extend the basic co-localization analysis by including the orientations of the structures on which the molecules reside. We refer to the combination of co-localization of molecules and orientational alignment of the structures on which they reside as co-orientation. Because the orientation varies with the length scale at which it is evaluated, we consider this scale as a separate informative dimension in the analysis. Additionally we introduce a data driven method for testing the statistical significance of the co-orientation and provide a method for visualizing the local co-orientation strength in images. We demonstrate our methods on simulated localization microscopy data of filamentous structures, as well as experimental images of similar structures acquired with localization microscopy in different color channels. We also show that in cultured primary HUVEC endothelial cells, filaments of the intermediate filament vimentin run close to and parallel with microtubuli. In contrast, no co-orientation was found between keratin and actin filaments. Co-orientation between vimentin and tubulin was also observed in an endothelial cell line, albeit to a lesser extent, but not in 3T3 fibroblasts. These data therefore suggest that microtubuli functionally interact with the vimentin network in a cell-type specific manner.
Subject(s)
Human Umbilical Vein Endothelial Cells/metabolism , Intermediate Filaments/metabolism , Tubulin/metabolism , Vimentin/metabolism , 3T3 Cells , Algorithms , Animals , Cell Line , Cells, Cultured , Computational Biology/methods , Computer Simulation , Fibroblasts/cytology , Fibroblasts/metabolism , Humans , Mice , Microscopy, Fluorescence , Models, Biological , Protein BindingABSTRACT
Quantification in localization microscopy with reversibly switchable fluorophores is severely hampered by the unknown number of switching cycles a fluorophore undergoes and the unknown stoichiometry of fluorophores on a marker such as an antibody. We overcome this problem by measuring the average number of localizations per fluorophore, or generally per fluorescently labeled site from the build-up of spatial image correlation during acquisition. To this end we employ a model for the interplay between the statistics of activation, bleaching, and labeling stoichiometry. We validated our method using single fluorophore labeled DNA oligomers and multiple-labeled neutravidin tetramers where we find a counting error of less than 17% without any calibration of transition rates. Furthermore, we demonstrated our quantification method on nanobody- and antibody-labeled biological specimens.
Subject(s)
Light , Microscopy, Fluorescence/methods , Staining and Labeling , Animals , Calibration , Chlorocebus aethiops , Cluster Analysis , Fluorescent Dyes/chemistry , Rats , Vero CellsABSTRACT
Inspired by recent developments in localization microscopy that applied averaging of identical particles in 2D for increasing the resolution even further, we discuss considerations for alignment (registration) methods for particles in general and for 3D in particular. We detail that traditional techniques for particle registration from cryo electron microscopy based on cross-correlation are not suitable, as the underlying image formation process is fundamentally different. We argue that only localizations, i.e. a set of coordinates with associated uncertainties, are recorded and not a continuous intensity distribution. We present a method that owes to this fact and that is inspired by the field of statistical pattern recognition. In particular we suggest to use an adapted version of the Bhattacharyya distance as a merit function for registration. We evaluate the method in simulations and demonstrate it on three-dimensional super-resolution data of Alexa 647 labelled to the Nup133 protein in the nuclear pore complex of Hela cells. From the simulations we find suggestions that for successful registration the localization uncertainty must be smaller than the distance between labeling sites on a particle. These suggestions are supported by theoretical considerations concerning the attainable resolution in localization microscopy and its scaling behavior as a function of labeling density and localization precision.
ABSTRACT
Resolution in optical nanoscopy (or super-resolution microscopy) depends on the localization uncertainty and density of single fluorescent labels and on the sample's spatial structure. Currently there is no integral, practical resolution measure that accounts for all factors. We introduce a measure based on Fourier ring correlation (FRC) that can be computed directly from an image. We demonstrate its validity and benefits on two-dimensional (2D) and 3D localization microscopy images of tubulin and actin filaments. Our FRC resolution method makes it possible to compare achieved resolutions in images taken with different nanoscopy methods, to optimize and rank different emitter localization and labeling strategies, to define a stopping criterion for data acquisition, to describe image anisotropy and heterogeneity, and even to estimate the average number of localizations per emitter. Our findings challenge the current focus on obtaining the best localization precision, showing instead how the best image resolution can be achieved as fast as possible.
