Worm-align and Worm_CP, Two Open-Source Pipelines for Straightening and Quantification of Fluorescence Image Data Obtained from Caenorhabditis elegans

We describe here a simple opensource Fiji-based workflow named Worm-align, which can be used to generate single or multi-channel montages of straightened worms of interest from raw microscopy images. Because this workflow relies on user selected animals of interest, it might be particularly useful when analyzing images from C.elegans where the worms are not all at the correct stage or condition. It should be noted that the output of Worm-align can be used for subsequent quantification of fluorescence with either Fiji or other image analysis software.

Here we demonstrate fluorescence quantification using the CellProfiler pipeline Worm_CP. Begin by creating a mouth micropipette by extending a thin glass capillary in the flame of a Bunsen burner. After extension in the flame, break the capillary into two pieces if it didn't break into two pieces after extension.

If it broke into two pieces, cut the end of the longest one. Select the longer piece and test whether the capillary is open by attempting to aspirate water. Detach the adapter from a three millimeter silicone tube.

Plug the glass capillary into a capillary adapter linked to a six millimeter silicone tube. Then plug the other end of the six millimeter tube into a 0.2 micrometer filter and a three millimeter silicone tube on its other end. Plug a one millimeter filter tip into the free end of the three millimeter silicone tube to aspirate liquid.

Under a dissection microscope, remove as much liquid as possible around a pellet of fixed worms with the mouth micropipette. Quickly add 10 microliters of mounting medium to the bottom of the tube. Rinse a 10 microliter tip in PBS with traces of detergent to prevent worms from sticking to the sides of the plastic pipette tip.

Then cut the very end of the tip with a pair of scissors. Transfer eight microliters of mounting medium with the worms onto a previously prepared agarose pad. While observing the slide under the microscope, gently agitate it to avoid overlap of the worms.

Then cover the drop of mounting medium on the agarose pad with an 18 by 18 millimeter coverslip. To mount live worms, pipette three to four microliters of three millimolar levamisole dissolved in M9 onto an agarose pad. Pick 30 to 50 worms per condition into the drop of levamisole.

Then cover the drop with an 18 by 18 millimeter coverslip and image the worms within one hour. Install the open source image analysis software package Fiji from ImageJ, or if it's already installed on the computer, verify that it is version 1.52A or later, then download the Worm-align repository from GitHub and save it on the computer. Once all pipeline components have been downloaded and installed, open Fiji and execute the Worm-align macro by clicking plugins, macros, and run in the main menu bar.

Locate the Worm-align. ijm script and click open. Navigate to the input folder with the images to be analyzed and click select, making sure that the selected folder only contains image files.

The macro will automatically generate an output folder where all results will be saved. The name of the folder will be the same as the input folder with output as a post-fix. Allow the macro to open the first image in the input folder and use it as a representative image to extract the settings required to generate the montage, including the width of the worms, the brightness, and the contrast.

Using the straight line drawing tool, draw a line across the width of a worm and click OK.Use the length of this line to determine the height of the cropped regions for single worms. For each channel, specify the name, lookup table, and whether it should be included in the montage, then click OK.Next, adjust the brightness and contrast settings for the channels using the sliders. Repeat this process for the remaining channels.

Once all settings have been configured, they'll be recorded in a settings table and saved to the CellProfiler subfolder of the output folder. An image is generated to show what all images will look like after application of the settings. If the image is satisfactory, tick the top box.

The second and third box of the check all settings panel specify the options for montage generation. Leave both boxes ticked and click OK to execute the rest of the macro. Failure to tick the top box will cause the macro to rerun the setup.

The macro then proceeds to open all images in the input folder. For each image, draw lines on the longitudinal axis of all worms to be included in the montage by using the segmented or the freehand line tool. Draw lines consistently from head to tail or vice versa along the full length of the worms and add each line to the ROI manager by clicking Control T.Once all desired worms have been added, click OK.Worm-align will then generate cropped images of single selected worms, which will be saved in the single worm subfolder of the output folder.

Montages of all worms selected will be saved in the aligned folder. Download and install CellProfiler 2.2.0 by clicking the link for previous CellProfiler releases on the download page and selecting the required operating system. Before starting the Worm_CP pipeline, ensure that all expected output images are present in the CellProfiler subfolder of the Worm-align output folder.

A processed copy of the original image, a binary image mask of the worm population, align mask if the line is drawn on selected worms and one image representing each of the channels in the original image should be present. Open CellProfiler, then click on the images input module and drag the CellProfiler module folder into the window that says drop files and folders here. If a list of images is present from a previous analysis, first remove these by right-clicking in the window and selecting clear file list.

Click on the metadata input module and on the second extraction method, click on the yellow folder and navigate to the CellProfiler subfolder of the Worm-align output folder. Select the settings file, then click update. Next, click on the names and types input module, and make sure that all images required for the pipeline are present.

Before running the pipeline, select a destination for the output results in the output module. Use the test mode to see how the pipeline performs by clicking start test mode and allow it to run through the first image in the folder. When satisfied with the performance of the pipeline, click exit test mode and analyze images.

Before beginning analysis, make sure that all eyes in front of the analysis module are closed. When analysis is complete, open the Worm_CP output folder that consists of two CSV files, worms CSV and lines CSV. Culturing and imaging C.elegans according to the method described in this protocol produces large overview images of worm populations.

The output of the pipeline largely depends on the quality of the lines drawn on top of the images. Several line examples and their output from Worm-align are shown here. When using the Worm-align script, visual identification of intersecting worms is possible from the overlay images found in the data subfolder, as well as from the panels of individual worms in the montage.

The QC table can also be used to identify overlapping worms. However, intersecting lines are problematic for the Worm_CP pipeline. This is because Worm_CP uses line mask, not regions of interest, to help identify individual worms.

Therefore, CellProfiler will segment one of the worms as two objects. The Worm_CP pipeline has been used to quantify fluorescence intensity from fixed animals labeled with a fluorescent dye that incorporates into lipid droplets. The lipid droplet content is decreased by 17%between wild type and mutant DBL1 animals using manual quantification, and by 12%using the Worm_CP pipeline.

Worm_CP was also used to quantify the heat shock response in live worms expressing GFP under control of a heat shock inducible gene. In the absence of heat stress, the worms did not induce GFP expression. When the worms are exposed as a short heat shock, GFP expression is induced.

The output of Worm_CP depends largely on the quality of the lines you draw using Worm-align. Make sure that your lines are not touching or overlapping and draw all your lines in the same direction. Checking the QC table can help you identify lines that are touching or overlapping so you can exclude those cases from your analysis.

The output of Worm-align can be used for subsequent quantification either in Fiji or in other image analysis software packages. We have shown here a very basic CellProfiler pipeline into which other analysis modules could very easily be incorporated, for instance, to count the number of lipid droplets or to quantify the intensity of individual droplets within a worm. One of the advantage of this technique is a possibility to quantify fluorescence from individual worms rapidly.

In our lab, we have an interest in individual viability using fluorescence reporters and we use Worm-align and Worm_CP routinely for this purpose.