With the PLA approach, since each dot represents a high concentration of fluorescence (several hundred–fold replication of the DNA circle) as a result of the probe proximity, the dot number can be quantified independently of the intensity. The fluorescent particle analysis was performed and automated with ImageJ software (https://imagej.nih.gov/ij/). The script for .dv images (DeltaVision) is presented in Table 2. The two channels (for instance DAPI and TRITC) were separated to analyze the image from DAPI-nuclear staining separately from the image of the TRITC-channel associated to the PLA dots. First, on the DAPI-channel image, the filter "Smooth" surface was applied to the image. Then, the best threshold was set to identify nucleus and to convert the image to binary (black and white) image. To help separating touching nuclei, morphological functions were processed as followed: "Close" command (i.e. a "Dilation" operation followed by "Erosion", to fill nuclei) and "Open" command (i.e. "Erosion" operation followed by "Dilation", to smooth the image and remove isolated pixels). The overlapping nuclei were separated using the "Watershed" function. The "Analyze particles" command was used to count the number of separated nuclei on the image, and results were added to ROI (region of interest) manager. In this step, the appropriate minimum and maximum pixel area sizes was set and cells on picture edge were excluded.Table 2ImageJ SCRIPT for .dv image (DeltaVision format) analysisSTEPSSCRIPT1. Separate the different channels (C1- for DAPI-nuclear staining and C2- for TRITC-channel associated to the PLA dots)- imageName = getTitle();- run (“Split Channels”);- selectWindow (“C1-” + imageName);- selectWindow (“C2-” + imageName);- selectWindow (“C1-” + imageName);- run (“Smooth”);- run (“Median...”, “radius = 2”);2. Apply threshold on C1- setAutoThreshold (“Default dark”);- //run (“Threshold...”);- setOption (“BlackBackground”, false);- run (“Convert to Mask”);3. Apply morphological filters on C1- selectWindow (“C1-” + imageName);- run (“Close-”);- run (“Open”);4. Segment nuclei on C1- run (“Watershed”);- run (“Sharpen”);- run (“Clear Results”);5. Count individual nuclear staining on C1- run (“Analyze Particles...”, “size = 75–550 show = [Overlay Outlines] exclude clear add”);6. Count individual PLA dots on C2- selectWindow (“C2-” + imageName);- run (“Find Maxima...”, “noise = 60 output = [Single Points] exclude”);- selectWindow (“C2-” + imageName + “Maxima”);7. Divide by 255 on the “find maxima output”- run (“Divide...”, “value = 255”);- run (“Set Measurements...”, “area integrated redirect = None decimal = 3”);8. Measure the pixel values- roiManager (“Measure”);9. Get the results of the number of PLA dots in each nucleus- String.copyResults();- selectWindow (“C2-” + imageName + “Maxima”);- close();