Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools

The overall goal of using image analysis software and developmental biology is to obtain quantitative data for mechanistic models of biological processes. This method can help answer key questions in developmental biology, such as how can mutant pheno phenotypes be quantitatively analyzed? The main advantage of this methodology is that it provides researchers with the ability to identify alterations in biological processes and developmental phenomena in an unbiased way.

Though this method can be used to provide insight into development and morphogenesis of sea elegance, it can also be applied to other model organisms such as josepha, Demonstrating the reconstruction of cell shape with IOD will be CINA Leman, a PhD student in my laboratory. After installing the IM MOD program, open the eunuch shell and type in Im mod in the IM mod window. Select the file with the appropriate raw data from which to generate a 3D model and use the information window to locate the bottom and top of the objects in the zap window.

In the information window, again, trace the cell outlines creating the first contour at the top plane of each cell and taking care to create a new object for each cell. Then scroll down in Z and create a new contour for each Z plane, and subsequently create a new object for each cell. After outlining as many cells as appropriate for the model, open the model view window to inspect the objects and their contours.

Then in the model view toolbar, choose edit and objects. The respective editing window will open to model all of the cells as filled and closed objects. Choose mesh as the draw data type and fill as the drawing style.

Click on meshing and check the option cap. Then check as many objects as necessary and click mesh. All the program will generate solid objects from the stacks of contours.

Change the Z scale in the view window to adjust the Z sampling factor as necessary. Then under the edit menu, select view to rotate the 3D objects, saving snapshots or movies of the cells as appropriate to track objects from fluorescent time-lapse recordings. Using NDR first, convert the raw data into a TIFF file.

Then open the file. In end drop. Select the 2D viewer icon and click on the fit range icon to adjust the histogram under the data menu.

Select file, name, image, set, channel, and set X, Y, Z resolution and enter the X, Y, and Z values. To annotate the nuclei, move to the plane of interest and select the 2D viewer again. Then select lineage from the dropdown menu and choose new lineage.

Click and drag on the nucleus of interest to market. Then right click on the nucleus and choose rename particle. From the dropdown menu, enter a name for the particle and then drag the arrow icon to change the diameter of the circle.

Next, click on the right icon to mark the central plane of the nucleus. Then to proceed in time and plane, choose the frame and Z options at the bottom toolbar and adjust the position or size of the circle that marks the nucleus accordingly until the tracked cell divides. When a cell division is observed, mark the daughter nuclei and click on the windows icon to switch to lineage.

Viewer mark all three nuclei simultaneously and select associate parent under the lineage option. Then when all of the cells have been tracked, click on the file name and switch to the channel. Marking the cell division remnant to quantitatively analyze cortical flow using particle image velocity symmetry software.

Load the new image files in pif lab and select the sequencing style. 1, 2, 2, 3. Next, navigate to the directory containing the sequence of desired images.

Select the images and click add to import the images. Then under analysis settings, select exclusions. ROI mask and use the button.

Draw masks for current frame to inactivate the undesired part of the images under the analysis settings. Again, select PIF settings and choose fast Fourier transformation window deformation as the desired PIF algorithm. For pass one, enter an interrogation area value of 64 pixels with a step of 32 pass two.

Enter an interrogation area value of 32 pixels with a step of 16. Then select linear from the window deformation dropdown menu and choose the Gaussian two by three point method for sub pixel displacement estimation. Now select analyze from the analysis menu and select analyze all frames post-processing, select vector validation from the post-processing menu and apply a standard deviation filter threshold of seven to all of the frames from the plot menu.

Select derived parameters. Modify data followed by vectors, pixels per frame, and adjust the smoothness of the vectors and high pass filter. After applying these adjustments to all of the frames, set the used frames to one to end.

Finally click on the calculate mean vectors button to measure the mean vectors of all of the frames focusing on the turn of the gonad of wild type C elegance adults imaged as just demonstrated. A 3D model of the germ cells is generated from the microscopy data, allowing analysis of the changes in cell size that occur while the cells transit from the distal to the proximal arm of the cus using two color time-lapse microscopy. The models obtained by line histone fusion proteins and non-muscle myosin in NDR illustrate the stereotyped pattern of cell division remnant inheritance.

Moreover, from the line data, the tracks for each cell L and cell division remnant and the correlation to the cell division timing can be obtained in this experiment. Short-term time-lapse microscopy with high temporal resolution of cortical non-muscle myosin two was performed to evaluate differences in the dynamics of cortical polarizing flow between wild type an embryos depleted for the row gtpa activating protein RGA three as expected. The flow in the wild type embryos was predominantly along the long axis of the embryo.

While the flow in the RGA three RNA interference embryo was orthogonal to this axis as easily apparent from the PIP analysis. Once mastered manual segmentation of complex objects and cell tracking during embryonic development can be done within a few hours if properly, while attempting to Perform cell and object tracking. It's important to remember to set up appropriate temporal resolution so as not to lose the object during the analysis Using the three tools described here.

Statistical analysis can also be performed to answer the questions about variability or just to compare different embryos. Implementing quantitative image analysis software enables us and other developmental biologists like us to explore morphogenetic mechanisms of development at an unprecedented level of detail. After watching this video, you should have a good understanding of how to use a diverse set of software tools to perform quantitative image analysis.