Many biological studies involve the interaction of various objects within the biological system. In Imaris, we provide both intensity based and object based colocalization for studying these interactions.
In this example, we want to know the percentage of green vesicles that colocalize with red vesicles. I will perform both intensity-based as well as object based coloc to answer this question.
Let's start with intensity based coloc. Go to ‘Coloc’, and specify Green as Channel A, Red as channel B. We will input the intensity threshold that best represent the vesicle signal level for both channels.
Click ‘Build Coloc Channel’ to save the result as a new channel. We can check the colocalization statistics from ‘Display adjustment’ > ‘Colocalization result’. Under ‘Coloc Estimated Statiscs’ tab, Imaris provides several commonly used coloc values. The one that is most relevant to our question of vesicle colocalization is ‘% of volume A above threshold colocalized’, for the percentage of green vesicles overlapping with red vesicles.
While intensity based coloc has very straightforward workflow, it has several limitations.
First, determining the intensity threshold can be subjective, and the intensity value may suffer from auto-fluorescence, bleed-through, background noise, or other variations from image acquisition.
Second, the information it provides is in the unit of voxel, rather than in biologically defined structures.
Furthermore, intensity based coloc also strictly measures the co-existence or co-variance of the intensity within the same voxel. It cannot capture the colocalization defined by object proximity that may not have signal overlap in voxel.
Let’s switch gear to object based coloc.
The first step is to perform spot detection to define both green vesicles and red vesicles.
Here I already have red vesicles created. Let’s go ahead to create green vesicles.
At ‘Classification’ step, we can utilize the ‘Shortest distance to Spots’ to define Colocalized spots based on their distance to the other Spots object. We will name one class as ‘Coloc’, another one ‘Not coloc’
Here I define the distance within 1 um or less as colocalized.
The result can be found under Statistics tab, where we can review our analysis in a more biologically relevant unit, as in this case, the number of vesicles rather than the number of voxels.