Here I am again with a new project: I am looking at two cell types (A2 and M1) with a variety of treatments, each within the confluent monolayer and at the margin of a scratch wound (the treatments affect, among others, motility). I have stained nuclei (blue, channel _C001), actin (green, channel _C002) and several proteins, each in red (as in the uploaded examples, channel _C003), and I also have the corresponding DIC (channel _C004), all in confocal.
As you can see, the morphology of the cells are quite different, and even more so when they start migrating into the wound.
I also observed there is some kind of correlation (sometimes inverse) between:
a. The amount (I would say integrated intensity) of actin and that of some of the proteins;
b. Actin organization (more stress fibers – i.e., fibrillar – vs. more diffuse – i.e., granular, and the granules of varying size) and treatment;
c. Actin and some of the proteins cytosolic (at in one case nuclear) localization.
I am thus faced with the following problems:
- Detect correct cell boundaries; I would use both the DIC and the actin staining, but I don’t know how to use DIC images and how to combine them with the fluorescent ones in order to get as close to reality as possible secondary objects (cells). Also, would MeasureObjectSizeShape be able to tell me something about the highly polymorph A2 cells migrating into the wound? (that is, not just width/length or similar; this morphology changes with treatment).
- How to get measurements of actin organization? (fibrilar vs. granular?) I don’t know which of MeasureGranularity or MeasureTexture is more appropriate in this case, since I also need to know the amount of fibrilar actin (stress fibers).
- I guess that if I get integrated intensity measurements (per cell) for actin and my proteins, MeasureCorrelation would tell me if there is a direct/inverse/no correlation between these measurement in each cell; correct?
- However, I also need to see if I have, say, more of my protein when actin is more fibrilar, and if there is a co-localization or on the contrary, the proteins are to be found more in regions with less actin. I’m at a loss here…
All these are quite subtle, and that’s why I need numbers to support (or not) my hypotheses. Can you please help with suggestions on how to built a pipeline(s) for any or all of these?
PS. For some reason I could not attach the files, so here is a link to Dropbox:
dropbox.com/sh/7j1yxmr225w3 … nrIna?dl=0