Quantification of processing bodies using CellProfiler analysis.

CellProfiler (https://cellprofiler.org) is an open-source software for high-content image analysis (142) and was used to develop an unbiased method for quantifying changes to PB dynamics. The pipeline used for quantifying PBs was structured as follows. To detect nuclei, the DAPI image was thresholded into a binary image. In the binary image, primary objects between 30 to 200 pixels in diameter were detected and defined as nuclei. Cells were identified as secondary objects in the WGA image using a propagation function from the identified nuclei, which determined the cell’s outer edge. Using the parameters of a defined nucleus and cell border, the cytoplasm was then defined as a tertiary object. The EDC4 channel image was enhanced using an “enhance speckles” function to identify distinct puncta and eliminate background staining. The cytoplasm image was then applied as a mask to the enhanced puncta image to ensure quantitation of only cytoplasmic puncta. EDC4 puncta were measured in the cytoplasm of cells using a “global thresholding with robust background adjustments” function as defined by the program. The threshold cutoff for identified EDC4 puncta remained constant between all experiments with identical staining parameters. Puncta number per cell, intensity, and locations with respect to the nucleus were measured and exported as csv files and analyzed in RStudio. Data were represented as fold change in EDC4 puncta count per cell normalized to the vector puncta count. “Relative EDC4 puncta/cell (KapB/vector)” demonstrates the KapB puncta count divided by vector puncta count, a ratio that was calculated within each treatment group for each biological replicate.