I’m currently working with C2C12 muscle cells. They are originally myoblasts and then over time, they fuse with other single cells and form a myotube. These myotubes by definition contain 2 or more nuclei and are positive for myosin heavy chain (MHC, in the green channel) antibody. On the other hand, myoblasts, which contain only one nucleus, are not MHC positive and therefore do not have any signal in the green channel.
I’m trying to count the total number of nuclei within each myotube. I am also interested in getting the ratio of nuclei within myotubes to the total number of nuclei in the field (within myoblasts or myotubes).
I was thinking to use a strategy to first identify nuclei, and then cytoplasms, and finally count the number of nuclei per cytoplasms. Unfortunately, I couldn’t find a way to let Cell Profiler allow more than one primary object per secondary object.
If there is a way, let me know!
My compromise is to consider myotubes as uni-nucleated cells with MHC signal.
So I have set up cell profiler to first identify all the nuclei with DAPI, then have the program find the myoblast by their absence of signal in the green channel. Once the program has identified the primary and the secondary, I have the program find the cytoplasm, by subtracting the primary channel from the secondary channel. The program then measures the intensity of the Green channel and Filters objects by Intensity from the cytoplasm, the criteria used is the Integrated Intensity Edge set to 19-20.
Now the first image I used to test the Pipeline gives satisfactory numbers (close to manually counted), but when I analyze a second image, the program misses a lot of the nuclei found within a myotube. I have images saved from the Cell Profiler Program, they are on Picassa Images from CellProfiler, the ones starting with 01 are the first image, and the ones with 02 are the second image (The File names are descriptive enough I think). I have taken the images generated by cell profiler at the PrimaryIdentifyAutomatic (nuclei), SecondaryIdentify (Myotubes), TertiaryIdentify (Cytoplasm) and FilterObjectbyMeasurement (Nuclei found within a Myotube).
See below the custom settings of some of the module within my pipeline
Thanks in advance for any input!
-Discard objects outside of diameter range : No
-For Propagation, enter regulization factor: 0.001
-Category of Measurement: Intensity
-Minimum Value: 19
-Maximum Value: No Maximum