Semi-automated analysis of podosome reformation using ImageJ
Here, we describe assays that enable the measurement of podosome dynamics, namely reformation of podosomes, in fixed cells. The assay is based on the key influence of Src kinase on podosome formation and turnover, and use the general Src kinase inhibitor PP2 as a tool to disrupt podosomes (Linder et al. J. Cell Sci.,2000), which enables the analysis of synchronised reformation of podosomes.
Subsequent software-based image analysis facilitates quantification of cells and podosomes and allows statistical analysis, yielding parameters such as the number of podosomes per cell and podosome density.
In the first step, images acquired in the “cell channel” (HCS CellMask, Red stain) are processed in order to get a final mask corresponding to all whole cells present in the respective field of view. For this purpose, it is important to reduce the background noise as much as possible, to ease the subsequent segmentation step, which enables recognition of individual cells as objects by the software. All settings can be adapted depending on the user needs and the quality of the staining.
The following steps (in Italics) have been recorded in a macro.txt using ImageJ (http://rsbweb.nih.gov/ij/), therefore can be copy/pasted in a .txt file and then opened with ImageJ or carried out one by one manually (using the respective tools).
Clearly all the steps can be fine tuned, depending on the microscope settings and/or the user needs, and the basic imaging principles can be used with any imaging software.
It’s very important to calibrate the scale depending on the microscope settings, before applying any imaging tool !
Cell mask macro steps:
run(“Gaussian Blur…”, “sigma=4″);
run(“Analyze Particles…”, “size=150-Infinity circularity=0.30-1.00 show=Masks clear exclude add”);
This includes combining two segmented objects belonging to one single cell in case of oversegmentation (select the ROIs that need to be merged, right-click and select the “OR (Combine)” function followed by “Add”; this will create a single new ROI that will include the previously selected ones, which have to be deleted individually).
Moreover you can now set the values for calculation, for example cell area (Analyze>Set Measurements…>check only “Area”), then manually select all ROIs and click on “Measure”.
The obtained area values can be saved in a spreadsheet.
Once the ROIs corresponding to the cell positions are recorded, open the “podosome channel” (phalloidin stain) of the same image and run a series of actions which will allow highlighting and better definition of podosomes as individual, countable objects.
Podosome macro steps:
run(“Subtract Background…”, “rolling=5″);
run(“Convolve…”, “text1=[-1 -1 -1 -1 -1\n-1 -1 -1 -1 -1\n-1 -1 30 -1 -1\n-1 -1 -1 -1 -1\n-1 -1 -1 -1 -1\n] normalize”);
run(“Analyze Particles…”, “size=0.10-50 circularity=0.80-1.00 show=Masks display”);
n = roiManager(“count”);
for (i=0; i
After applying for a single picture these two macros, it will be possible to save the number of podosomes detected in each identified cell. These values, in combination with the values for cell area, can be used to calculate podosome density (here defined as number of podosomes/100 µm2 of cell covered area).