Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Here we present a protocol to assess the organization of astrocytic networks. The described method minimizes bias to provide descriptive measures of these networks such as cell count, size, area, and position within a nucleus. Anisotropy is assessed with a vectorial analysis.

This method can help answer key questions regarding the organization of astrocytic networks in brain structures. The main advantage of this technique is that it proposes an unbiased method to count label cells and document their anatomical organization within a defined structure. Open ImageJFIJI, select the desired file, and click OK in the bio-format's import options window.

To redefine a Z stack that will contain only the optical slices needed for the final Z stack, first select STK and Z project, and then click on the stack knob in the tool bar. Select max intensity in the projection type setting. Save the file, and name it stack file.

If the imaging file contains several channels, use image color and split channels to show only the channel with the image of the astrocytic network. Check the pixel settings of the image by selecting image, properties, pixel, with one for pixel dimension. Then use the subtract background tool by opening process and subtract background to remove background biocytin labeling.

Use the preview function to set the rolling ball radius, which is generally set at 50 pixels. If further noise reduction is required following the subtract background step, select process, noise, and remove outliers. Select bright in the which outliers setting, and use the preview function to set the radius and threshold.

Be careful using the remove outlier tool, since it may blur the data, as shown here. Adjust the threshold using image, adjust, threshold. Select default and B and W mode.

Click on apply. Convert the image into a binary image with the binary process tool by selecting process, binary, and make binary. Save the file as a tiff file and name it binary file.

To count cells, first set the measurement type by clicking analyze and set measurement. Then select the centroid option. Ensure that the binary file is open onscreen.

Again, open the analyze menu, and this time select analyze particles. Next, select show and outlines. This generates a new file that shows the result of the detection.

Optimize the parameters to refine the detection. To detect cells only, use a size value between 30 and 6000, and circularity between zero to one, where one defines a perfect circle and zero a random shape. Run the detection by clicking OK.Two tables will appear, a table titled summary that provides the number of detected cells, and a table titled results that provides the X and Y coordinates of each cell.

Copy the values and paste them into a spreadsheet application. Save this table under the name detection table. A file with a plot of detected cells will also appear.

Save this file as a tiff file under the name detection file. If a group of two or more labeled cells are detected as a single cell with the analyze particles tool, use the watershed tool on the binary image by selecting process, binary, and watershed before applying the analyze particles tool. To measure the surface area of the networks, use the detection file in ImageJ.

Left click the mouse to select the polygon selection tool in the toolbar. Left click again to begin tracing a region of interest, or ROI, that connects all the cells located in the external periphery of the network. Right click to close the polygon.

Open the set measurement window and select the area option. Then open the ROI manager and add the traced polygon in the ROI manager by clicking add. Run the measurement by clicking measure in the ROI manager.

The area measurement will appear in a table and be expressed in pixels. Don't forget to convert this value with a conversion factor for the microscope used to obtain the value in square micrometers. Open the stack file in ImageJFIJI and identify the patched cell with its stronger labeling intensity.

Then open the file named detection table in a spreadsheet application, and find the number associated with the patched cell and its corresponding coordinates. If unable to accurately determine the patched cell, use the polygon tool to surround the area where the deposit of biocytin is denser, and refer to this position as that of the patched cell. Use the ROI manager as before to draw an ROI at the patched cell location and add it to the ROI manager.

Next, set the measurement and select the centroid option. In the RIO manager, click on measure to obtain the coordinates of the centroid of the traced area. Use these coordinates as the reference point for this specific network.

Use this formula to calculate the coordinates of each cell in reference to the patched astrocyte. Expressing the coordinates of each cell in reference to the patched astrocyte is an important step to calculate vector from the patched astrocytes. Use this formula to calculate the coordinates of the main vector of preferential orientation.

The main vector of preferential orientation of the network is the sum of all the previously calculated vectors for each cell comprised in the network. Divide the length of the main vector by the number of the cells in the network, minus one to exclude the patched cell, to normalize the values and enable comparisons between networks. To determine the position of each network in the nucleus of interest, first open the four x image with a vector image editor.

Multiply the dimensions in the dimension window by five to increase the size of the four x image. Here, the image was sampled at 800 by 800 pixels, and so the sampling resolution is changed to 4000 by 4000 pixels. Export the file in tiff format and name it resized four x.

Align the top left corner of the resized four x image with the bottom left corner of the Adobe Illustrator document. The software provides coordinates from a bottom left corner referential point. Open the 20 x image of the network.

Use the binary file or detection file because they are easier to align. Then, play with the opacity tool on the binary file of the 20 x image to align it with the resized four x image. When the alignment is done, select and hold the pipette tool so the measure tool appears, and select it in the left toolbar.

Use the measure tool to click on the top left corner of the 20 x image to get the coordinates of the 20 x referential point onto the resized four x image. This 20 x referential coordinates are useful for expressing the position of each network on a schematic drawing of the nucleus. To sum up the data, normalization of the nucleus as a rectangle is used.

To do this, use the polygon tool to surround the nucleus in the resized four x image. Then open the ROI manager and add the drawn ROI. Use image with transparent lights if the borders of the nucleus cannot be seen, in which case remember to resize it first.

In set measurement, select the bounding rectangle option to calculate the smallest rectangle within the drawn nucleus. Finally, click measure, then follow the steps in the written protocol to express the labeled cells coordinates in a normalized nucleus represented by the bounding rectangle. A single astrocyte in the dorsal part of the trigeminal main sensory nucleus, labeled by SR101, was targeted for whole-cell recording and filled with 0.2%biocytin.

Electrical stimulation of the fifth tract increased biocytin labeling in the dorsal part of the trigeminal main sensory nucleus, representing an increase in the number of coupled cells. Astrocytic networks remain confined within the dorsal part of the trigeminal main sensory nucleus and their main orientation. This technique was developed to position astrocytic networks within a defined structure, but can be used to express the position of population of labeled cell in any structure.