Volumetric Imaging and Analysis of Primary Cilia in Musculoskeletal Tissue using the ARL13B-CENTRIN-2 Mouse Model

To better understand the growing limb, we studied the primary cilium, an organelle that plays a key role in regulating cells'response to their environment. To investigate the cilium's role in growth, we are imaging them within the growth plate, a layer of cartilage where new bone grows. The primary cilium is extremely small, less than five micrometers long, which makes it challenging to image, particularly in three dimensions.

Imaging it within matrix-rich, part-calcified tissues, such as cartilage and bone, only makes accurately exploring their presence, let alone position, orientation, and size, even harder. We can map the 3D organization of primary cilia in all cells within the growth plate, asking if ill cells assemble one where and how it is orientated with respect to tissue morphogenesis. Primary cilia have previously only been studied in 2D in growth plates or in very small numbers.

The endogenous fluorescent signals for the cilium and centrioles brings confidence of ciliary identification because of the high signal to noise and avoids the need for immunohistochemistry. This protocol also allows high throughput collective imaging of hundreds of cilia in the tissue, enabling us to spatially relate cilia to the events of morphogenesis we are studying. This imaging and analysis methodology can be applied to other tissues in order to map primary cilia across tissues and organs.

This will allow for a greater understanding of the link between primary cilia structure and function. To begin, take the prepared frozen cryo section of the mouse tissue and place the slide horizontally at room temperature to thaw. Wash the slide using a drop of PBS for three cycles of five minutes each to remove the sham.

Apply 10-micromolar DAPI solution onto the slide and stain for one minute. Then mount the sample, cover it with a cover slip, and leave it at room temperature overnight. Seal the edges of the cover slip using cover slip sealant.

To set up the confocal microscope, turn it on, open the software, and click on the System button. Under the Acquisition tab, click on Smart Setup to set up the channels and add the GFP, mCherry, and DAPI channels. Then select the ARI Scan option and the sR8-Y function from the ARI scan triangle between resolution and speed.

Click Best Signal, and then OK to confirm. In the Locate tab under Microscope Control, select the 40 times and 1.4 objective with oil immersion. Next, place the slide in the slide holder and bring the objective up until the oil touches the cover slip.

Then position the growth plate, or other region of interest, underneath the light path. In the Locate tab, click on Fluorescence and select DAPI. And using the eyepiece, move the slide holder with the joystick to position the growth plate, or region of interest, under the field of view.

In the Acquisition tab, select only the DAPI channel. Click on Continuous to view the image of the DAPI channel on the screen and ensure the growth plate is visible. To open the tile viewer, click Show Viewer in the Tiles tab.

Add the required number of tiles, typically one tile in the X direction and three to five tiles in the Y direction. Then click Preview and Start. Now check that the tiles cover the three zones of the growth plate, resting, proliferation, and hypertrophic.

Adjust the tile position and number if necessary. To set up the image parameters, in the Acquisition tab, click on Continuous. To align the ARI scan detector, open the ARI Scan Detector Adjustment Window by clicking the tiled rosette symbol at the bottom.

Wait until all tiles turn green. In the Channels tab, adjust the gain master and laser power to clearly view the nuclei on the screen. Next, select all three channels and click on Continuous to start imaging.

Allow the ARI scan detector to align. In the Acquisition Mode tab, define the image size, pixel size, frame size, speed, and averaging values. In the Acquisition tab, select the Z-Stack tick box to enable Z-stack imaging.

Then select only the DAPI channel and click on Continuous to view the image on the screen. Move the objective down to the closest plane to be imaged. In the Z-Stack tab, click on Set First Plane, then focus away to the last plane to be viewed, and click on Set Last Plane to configure the imaging range.

Set the interval between Z-stack planes to 0.15 micrometers. Move to the center of the Z-stack imaging range. In the Tiles tab under Tile Regions, click on Verify and then on Set Z and Move to Next.

Now in the Focus strategy tab, confirm that the focus strategy is set to use Z-values and focus surface defined in the tile setup. Then click on Start Experiment to begin image acquisition. To process the images, go to the Processing tab, select Single or Batch Mode, select ARI Scan Processing, tick the 3D Processing option, and select Standard Auto Filter.

Choose the raw image acquired and start the processing. After completing ARI scan processing, select Stitching in the processing methods. Choose New Output, Fuse Tiles, Correct Shading, and All by Reference with the reference set as DAPI.

Select the ARI scan processed image and start the stitching process. To begin, import the acquired CZI image file into the software and open the Analysis panel. In the dropdown menu, select New Pipeline.

Use the Add Operation button to add operators to the pipeline. To create a cell detection pipeline, import the cell post Python segmenter into the pipeline. Set model name to Cyto 2, input channel to 2, second channel to 3, diameter in micrometers to 10.

flow threshold to 0.4, and cell probability threshold to 0. Next, add an import document objects operator before the pipeline and rename it to Import Manual Labels. Then add an object feature filter operator after the pipeline and rename it to Size Filter.

Draw region of interest using the Polygon tool on the first plane and the last plane. Rename the created object and tag it. Click on the forward blue arrow at the top of the Analysis panel to run the pipeline.

To create a primary cilia and centriole detection pipeline, open the Analysis panel and select New Pipeline from the dropdown menu. Add and adjust operators such as import document objects, two threshold operators, splitting, object, feature, filter, and compartment to the pipeline. Then click on the forward blue arrow at the top of the Analysis panel to run the pipeline.

Open the Objects window, select the object containing the cells, primary cilia, and centrioles, here named compartment cell, and click on Import/Export. Select Excel Export. Choose the features such as number of children, name, parent names, 3D oriented bound short side, middle side, long side, angle XY, angle XZ, angle YZ, bounding box X1, X2, Y1, Y2, Z1, Z2, size X, size Y, size Z, center of geometry X, Y, Z, plane first, last, count, mesh, volume mesh, and surface area mesh to save.

Primary cilia organization was successfully mapped in the growth plate of a six-week-old mouse. High resolution imaging demonstrated the ability to visualize individual centrioles and primary cilia in their three-dimensional environment. Cells and primary cilia are detected in 3D using the image analysis pipeline, which can differentiate primary cilia pointing to the side from those pointing backward.