The phenotype I am trying to analyze involves cell to cell fusion of human 293 cells. I would like to measure the degree of fusion shown in an image. In other words, I’d like to know the percentage of cells that are fused versus the percentage of cells that remain unfused ( or single cells). In the image below the GFP is a marker for the cytoplasm so all of the diffused green shown is a giant syncytium. Unfused cells are the brighter green spots and the black “holes” are just empty space on the dish. DAPI shows the nuclei. Could anyone suggest a pipeline or individual modules that would help with this? Much thanks!
A single pipeline in CellProfiler with UnmixColors or ColorsToGray may be possible, but as I tried myself, it may involve quite complex image filtering and morph.
So I would suggest you to try Ilastik with at least 4 classes of pixels:
- The bright green dots
- The blue dots
- The black holes
- The giant syncytium (dimmer green) near the black hole peripheral.
Then export the probability maps for each of these classes from ilastik and use them as inputs for CellProfiler (please do a search “ilastik” in the forum, there’re many examples)
The bright green dots will be the easiest targets, because they will stand out clearly.
You can then do a quick segmentation on green dots and blue dots in CellProfiler and count them, i.e. unfused cells over total numbers of cells.
You can also measure the areas of giant syncytium , and compare it with whole image area and black hole area to have an idea of how aggressive was the cell-fusion process.