Colocalization by cross-correlation, a new method of colocalization suited for super-resolution microscopy.

BACKGROUND: A common goal of scientific microscopic imaging is to determine if a spatial correlation exists between two imaged structures. This is generally accomplished by imaging fluorescently labeled structures and measuring their spatial correlation with a class of image analysis algorithms known as colocalization. However, the most commonly used methods of colocalization have strict limitations, such as requiring overlap in the fluorescent markers and reporting requirements for accurate interpretation of the data, that are often not met. Due to the development of novel super-resolution techniques, which reduce the overlap of the fluorescent signals, a new colocalization method is needed that does not have such strict requirements. RESULTS: In order to overcome the limitations of other colocalization algorithms, I developed a new ImageJ/Fiji plugin, Colocalization by cross-correlation (CCC). This method uses cross-correlation over space to identify spatial correlations as a function of distance, removing the overlap requirement and providing more comprehensive results. CCC is compatible with 3D and time-lapse images, and was designed to be easy to use. CCC also generates new images that only show the correlating labeled structures from the input images, a novel feature among the cross-correlating algorithms. CONCLUSIONS: CCC is a versatile, powerful, and easy to use colocalization and spatial correlation tool that is available through the Fiji update sites. Full and up to date documentation can be found at https://imagej.net/plugins/colocalization-by-cross-correlation . CCC source code is available at https://github.com/andmccall/Colocalization_by_Cross_Correlation .

Measuring Nanoscale Distances by Structured Illumination Microscopy and Image Cross-Correlation Spectroscopy (SIM-ICCS).

Since the introduction of super-resolution microscopy, there has been growing interest in quantifying the nanoscale spatial distributions of fluorescent probes to better understand cellular processes and their interactions. One way to check if distributions are correlated or not is to perform colocalization analysis of multi-color acquisitions. Among all the possible methods available to study and quantify the colocalization between multicolor images, there is image cross-correlation spectroscopy (ICCS). The main advantage of ICCS, in comparison with other co-localization techniques, is that it does not require pre-segmentation of the sample into single objects. Here we show that the combination of structured illumination microscopy (SIM) with ICCS (SIM-ICCS) is a simple approach to quantify colocalization and measure nanoscale distances from multi-color SIM images. We validate the SIM-ICCS analysis on SIM images of optical nanorulers, DNA-origami-based model samples containing fluorophores of different colors at a distance of 80 nm. The SIM-ICCS analysis is compared with an object-based analysis performed on the same samples. Finally, we show that SIM-ICCS can be used to quantify the nanoscale spatial distribution of functional nuclear sites in fixed cells.

Transport and accumulation of PVP-Hypericin in cancer and normal cells characterized by image correlation spectroscopy techniques.

PVP-Hypericin (PVP: polyvinylpyrrolidone) is a potent anti-cancer photosensitizer for photodynamic diagnosis (PDD) and therapy (PDT). However, cellular targets and mechanisms involved in the cancer-selectivity of the photosensitizer are not yet fully understood. This paper gives new insights into the differential transport and localization of PVP-Hypericin in cancer and normal cells which are essential to unravel the mechanisms of action and cancer-selectivity. Temporal (TICS) and spatiotemporal (STICS) image correlation spectroscopy are used for the assessment of PVP-Hypericin diffusion and/or velocity in the case of concerted flow in human cervical epithelial HeLa and human lung carcinoma A549 cells, as well as in human primary dendritic cells (DC) and human peripheral blood mononuclear cells (PBMC). Spatiotemporal image cross-correlation spectroscopy (STICCS) based on organelle specific fluorescent labeling is employed to study the accumulation of the photosensitizer in nucleus, mitochondria, early-endosomes and lysosomes of the cells and to assess the dynamics of co-migrating molecules. Whereas STICS and TICS did not show a remarkable difference between the dynamics of PVP-Hypericin in HeLa, A549 and DC cells, a significantly different diffusion rate of the photosensitizer was measured in PBMC. STICCS detected a stationary accumulation of PVP-Hypericin within the nucleus, mitochondria, early endosomes and lysosomes of HeLa and A549 cells. However, significant flow due to the directed motion of the organelles was detected. In contrast, no accumulation in the nucleus and mitochondria of DC and PBMC could be monitored.

Novel Tools to Measure Single Molecules Colocalization in Fluorescence Nanoscopy by Image Cross Correlation Spectroscopy.

Super Resolution Microscopy revolutionized the approach to the study of molecular interactions by providing new quantitative tools to describe the scale below 100 nanometers. Single Molecule Localization Microscopy (SMLM) reaches a spatial resolution less than 50 nm with a precision in calculating molecule coordinates between 10 and 20 nanometers. However new procedures are required to analyze data from the list of molecular coordinates created by SMLM. We propose new tools based on Image Cross Correlation Spectroscopy (ICCS) to quantify the colocalization of fluorescent signals at single molecule level. These analysis procedures have been inserted into an experimental pipeline to optimize the produced results. We show that Fluorescent NanoDiamonds targeted to an intracellular compartment can be employed (i) to correct spatial drift to maximize the localization precision and (ii) to register confocal and SMLM images in correlative multiresolution, multimodal imaging. We validated the ICCS based approach on defined biological control samples and showed its ability to quantitatively map area of interactions inside the cell. The produced results show that the ICCS analysis is an efficient tool to measure relative spatial distribution of different molecular species at the nanoscale.