Colocalization in Volocity 5.2

This is always a hectic time of year with exam papers to mark and meetings to attend, so it has been a while since my last tip. I have not been idle in the lab though!

In the Vipoir lab we are interested in seeing relationships and associations between our molecules of interest and we like the easy-to-use features of the colocalization view in Volocity. Imagine our delight then when Volocity 5.2 was released earlier this month, with powerful new colocalization tools to give us an even greater understanding of our results!

In its most basic sense, colocalization is described as the detection of signal at the same voxel location in each of two channels. But what we really want to see is how the intensity values of the signal in each channel relate to each other, to see if there is a correlation between the signal intensities that would indicate how our two molecules of interest are interacting with each other.

Let me show you how I perform a colocalization analysis in the new Volocity 5.2...

After opening my image sequence containing the two channels that I want to analyze, I select the colocalization tab at the top of my image view. I then check that I have the correct X and Y channels selected in the pop-down menu.

Volocity 5.2 colocalization

The colocalization view (above) shows me an extended focus merge of my two channels (X and Y) and a scatter plot that represents the intensity values of colocalized voxels found within the images. I am also presented with a clear list of statistics, including Pearson’s Correlation and Overlap Coefficients for the whole image, or for any regions of interest (ROI) that I have drawn on the scatter plot.

Colocalization statistics

It is very important to set thresholds so that voxels where both images show background intensity levels are not interpreted as colocalized. There are three ways in which I can do this:

  1. I can manually enter the values into the Threshold Maximum and Minimum boxes for each channel, or simply drag the slider controls on the scatter plot.
  2. I can use one of the ROI tools at the top of the screen to draw a ROI on the image preview. I then select Set Thresholds from ROI from the colocalization menu
  3. I can select Automatic Thresholding from the colocalization menu and Volocity will use statistical tests, using the method of Costes et al. (2004) to set thresholds objectively.

After setting thresholds, the only points left on the scatter plot are those that are positive for both x and y. These are the points that I am interested in as they allow me to see how the intensity values of the signal in each channel relate to each other.

Sometimes, I want to restrict my analysis to a specific ROI, or multiple ROIs, so as I can compare relationships between certain cells and/or structures of interest within those cells. When I select my ROI(s) on the preview, the statistics and scatter plot generated will be based only on those voxels which are within the ROI (and within the thresholds). If I do not select a ROI then the statistics and scatter plot will be based on the whole image.

I then select Generate Colocalization from the Colocalization menu and choose the output that I require.

By checking the Field statistics measurement box, I generate measurements that represent the whole volume, or the ROI(s) that I selected. I can choose to store these measurements as a new measurement item, or add them to an existing measurement item in my library. Volocity is always great at making things nice and easy for me! Each time point in my image sequence gives rise to one measurement row in my measurement table.

I can also choose to generate a scatter plot, which will be saved to a folder in my current library. I can then export this scatter plot to use in presentations or reports.

For simple visual illustration purposes, I can generate a merged channel. What is really exciting though is that Volocity 5.2 offers me an additional, improved way to visually identify colocalization through the generation of PDM channels. These are generated by calculating the product of the difference from the mean for each voxel from the two channels analyzed. Volocity generates a positive (colored yellow) and a negative (colored purple) PDM channel.

This gives me a clear visual display of the areas and the degree of positive and negative correlation and I can generate high quality colocalization images, great for publication!

I am heading back to the lab now, but for further explanation of the statistics that Volocity uses for colocalization, check out the following papers:
M. M. Manders, P. J. Verbeek & J. A. Aten (1993). Measurement of colocalization of objects in dual color confocal images. Journal of Microscopy. 169 (Pt 3): pp. 375-382.
S. V. Costes, D. Daelemans, E. H. Cho, Z. Dobbin, G. Pavlakis & S. Lockett (2004). Automatic and Quantitative Measurement of Protein-Protein Colocalization in Live Cells. Biophysical Journal. 86: pp. 3339-4003.