Nanoscale Distribution of Nuclear Sites by Super-Resolved Image Cross-Correlation Spectroscopy

Abstract

Deciphering the spatiotemporal coordination between nuclear functions is important to understand its role in the maintenance of human genome. In this context, super-resolution microscopy has gained considerable interest because it can be used to probe the spatial organization of functional sites in intact single-cell nuclei in the 20–250 nm range. Among the methods that quantify colocalization from multicolor images, image cross-correlation spectroscopy (ICCS) offers several advantages, namely it does not require a presegmentation of the image into objects and can be used to detect dynamic interactions. However, the combination of ICCS with super-resolution microscopy has not been explored yet. Here, we combine dual-color stimulated emission depletion (STED) nanoscopy with ICCS (STED-ICCS) to quantify the nanoscale distribution of functional nuclear sites. We show that super-resolved ICCS provides not only a value of the colocalized fraction but also the characteristic distances associated to correlated nuclear sites. As a validation, we quantify the nanoscale spatial distribution of three different pairs of functional nuclear sites in MCF10A cells. As expected, transcription foci and a transcriptionally repressive histone marker (H3K9me3) are not correlated. Conversely, nascent DNA replication foci and the proliferating cell nuclear antigen(PCNA) protein have a high level of proximity and are correlated at a nanometer distance scale that is close to the limit of our experimental approach. Finally, transcription foci are found at a distance of 130 nm from replication foci, indicating a spatial segregation at the nanoscale. Overall, our data demonstrate that STED-ICCS can be a powerful tool for the analysis of the nanoscale distribution of functional sites in the nucleus.

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

“…We chose the ImageJ plugin JACoP to perform the object analysis from which we get a list of coordinates of each center of mass detected in the image and a map of the center of mass, as shown in Figure 3 c. For each sample, we calculated a histogram of the values of distance between red and green particles, which we call a relative distance distribution (RDD) histogram. In the case of non-colocalizing samples, i.e., red and green particles distributed randomly in relation to each other, we expect to obtain a linear growing component due to simple geometrical considerations (i.e., at distance d from a given particle, there is a number of particles proportional to 2π d ) [ 29 ]. In the case of nanorulers, we obtain a peak of colocalization superimposed to a linear component ( Figure 3 d).…”

“…In ICCS, the amplitude and width of the cross-correlation function ( Figure 4 c) are compared to the corresponding parameters of the autocorrelation functions ( Figure 4 a,b) to extract (i) the fraction of the cross-correlated particles in the sample and (ii) information about the average distance between correlated particles ( Figure 4 a–c) [ 29 ]. Indeed, in super-resolved ICCS, the resulting shape of the cross-correlation function strictly depends on the spatial resolution achieved by the microscope in both channels and on the distance, d , between the two labeled molecules.…”

“…Oneto et al [ 29 ] provided an open-source code that was used in this work to perform Image correlation spectroscopy (ICS) and Image cross-correlation spectroscopy (ICCS) in MatLab (The Mathworks, Natick, MA, USA). The analysis is based on the calculation of spatial autocorrelation (ACF) and cross-correlation (CCF) functions.…”

“…The broadening of the cross-correlation function with respect to the autocorrelation functions was evaluated as Δw = w 12 -w cc with w cc = ((w 11 2 + w 22 2 )/2) 1/2 , and the Δw value was used to calculate a distance value d ICCS = (Δw/c) 1/2 , where c is a factor determined from simulated data, as explained in Oneto et al [ 29 ].…”

“…Therefore, ICCS can be used to investigate the spatial distribution of particle in images as a pixel-based method [ 27 , 28 ]. ICCS has been recently combined with super-resolved STED microscopy [ 29 ] to analyze the nanoscale spatial distribution of functional sites in the cell nucleus. Oneto et al have applied ICCS to dual-color STED images of nuclei in fixed cells.…”