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.

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.

No abstract

Chromatin in the nucleus is organized in functional sites at variable level of compaction. Structured illumination microscopy (SIM) can be used to generate three-dimensional super-resolution (SR) imaging of chromatin by changing in phase and in orientation a periodic line illumination pattern. The spatial frequency domain is the natural choice to process SIM raw data and to reconstruct an SR image. Using an alternative approach, we demonstrate that the additional spatial information encoded in the knowledge of the position of the illumination pattern can be efficiently decoded using a generalized version of separation of photon by lifetime tuning (SPLIT) that does not require lifetime measurements. In the resulting SPLIT-SIM, the SR image is obtained by isolating a fraction of the intensity corresponding to the center of the diffraction-limited point spread function. This extends the use of the SPLIT approach from stimulated emission depletion microscopy to SIM. The SPLIT-SIM algorithm is based only on phasor analysis and does not require deconvolution. We show that SPLIT-SIM can be used to generate SR images of chromatin organizational motifs with tunable resolution and can be a valuable tool for the imaging of functional sites in the nucleus.

High-density lipoprotein (HDL) is involved in the transport and metabolism of phospholipids, triglycerides, and cholesterol. Mimics of HDL are being explored as potential therapeutic agents for removing excess cholesterol from arterial plaques. Gold nanoparticles (AuNPs) functionalized

Quantifying the imaging performances in an unbiased way is of outmost importance in super-resolution microscopy. Here, we describe an algorithm based on image correlation spectroscopy (ICS) that can be used to assess the quality of super-resolution images. The algorithm is based on the calculation of an autocorrelation function and provides three different parameters: the width of the autocorrelation function, related to the spatial resolution; the brightness, related to the image contrast; the relative noise variance, related to the signal-to-noise ratio of the image. We use this algorithm to evaluate the quality of stimulated emission depletion (STED) images of DNA replication foci in U937 cells acquired under different imaging conditions. Increasing the STED power improves the resolution but may reduce the image contrast. Increasing the number of line averages improves the signal-to-noise ratio but facilitates the onset of photobleaching and subsequent reduction of the image contrast. Finally, we evaluate the performances of two different separation of photons by lifetime tuning (SPLIT) approaches: the method of tunable STED power and the commercially available Leica Tau-STED. We find that SPLIT provides an efficient way to improve the resolution and contrast in STED microscopy.

Quantifying the imaging performances in an unbiased way is of outmost importance in super-resolution microscopy. Here, we describe an algorithm based on image correlation spectroscopy (ICS) that can be used to assess the quality of super-resolution images. The algorithm is based on the calculation of an autocorrelation function and provides three different parameters: the width of the autocorrelation function, related to the spatial resolution; the brightness, related to the image contrast; the relative noise variance, related to the signal-to-noise ratio of the image. We use this algorithm to evaluate the quality of stimulated emission depletion (STED) images of DNA replication foci in U937 cells acquired under different imaging conditions. Increasing the STED depletion power improves the resolution but may reduce the image contrast. Increasing the number of line averages improves the signal-to-noise ratio but facilitates the onset of photobleaching and subsequent reduction of the image contrast. Finally, we evaluate the performances of two different separation of photons by lifetime tuning (SPLIT) approaches: the method of tunable STED depletion power and the commercially available Leica Tau-STED. We find that SPLIT provides an efficient way to improve the resolution and contrast in STED microscopy.

No abstract