High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

The overall goal of the Island Assay is to evaluate basic locomotor behavior of Drosophila melanogaster by means of automatic data processing and objective quantification. This method can be used to identify key regulators of locomotor behavior, such as genes implicated in movement disorders. It can be used to test drugs that may reverse such defects.

The main advantage of this technique is that allows high throughput quantification of Drosophila locomotor behavior, making this technique suitable for large scale screenings. We decided to develop this methodology to be able to analyze a large number of disease models. We were in need of automatized image data analysis to make this feasible.

Visual demonstration of this method is very helpful. Several steps of the beta processing are crucial, and might be difficult for new users, especially those not familiar with the software packages in use. First, prepare a minimum of three vials per experimental condition as biological replicates.

Each file should contain approximately 15 flies of the same gender and similar age. Importantly, the flies must have intact wings. Create the folders to store the experiments.

Generate these in a directory structure defined by the conditions and replicates. If, for example, the experiment has two genotypes with five replicates each, then create a main folder with the date of the experiment, and inside that folder, create one sub-folder for each genotype. Then, within the genotype folders, create sub-folders for each replicate.

Next, set up the test apparatus. Add cold water with a small amount of soap to the bath tray and position the platform in the middle of the bath, if not already fixed in the bath. Cover the tray and platform with a transparent box.

To illuminate the platform, position a cool lamp, such as ordinary 12 volt LEDs, above it. Also position a webcam connected to a computer directly above the platform. On the computer, open the image recording software.

From the menu system, select the appropriate webcam as the capture device. Place a dead fly on the island to adjust the video settings. Tweak the brightness, contrast, and color in the software so that the dead fly appears black against a white background.

Next, adjust the time lapse movie setup to save the movies as AVI files. Then, browse to the directory where the data should be saved, and define the name of the movie. Save these changes.

For compression of the image data, choose the Intel IYUV code. Set the recording speed to one frame every 0.1 seconds and adjust the corresponding playback rate to 10 images per second. Lastly, go to the advanced setting and select Create a bmp image for each captured frame.

Then, browse to the same directory that you have chosen to host the AVI files and press okay. Before beginning, make sure the island is empty and clean. Then, start the recording in the time lapse image interface of the image recording software.

Take a vial containing flies and tap it two or three times to knock all the flies down to the bottom. Then, quickly remove the plug from the vial and vigorously tap the flies onto the platform. They should all hit the platform at roughly the same time.

Give the flies up to 30 seconds to leave the platform, then stop the recording. If necessary, manually remove any remaining flies from the platform. Before proceeding to the next experiment, be certain to redefine the directory where the next set of data is to be stored.

The first task is to produce stacks and projections of the collected image series. In Fiji, open the Drosophila Island Assay. In the new window, enter the first image time series identifier.

Next, select only the create stack and projection sub-macro. Click okay, and direct the computer to the folder containing all of the sub-folders with individual Island Assay experiments. After processing the data, two new files will appear in each individual experimental sub-folder.

The next task is to define the exact location of the platform in the images. Open the graphical interface and select the define platform checkbox. Then, choose the directory where experimental sub-folders are stored.

The projection image and two windows will open. In the first image, draw a polygon over the island platform using the polygon selection tool. Do not include the border line at the parameter of the platform in this selection.

Add the selection to the ROI manager window by clicking add in the ROI manager window. After adding the selection to the ROI manager, it will appear as a set of values. Then, click okay in the define the platform window.

The software will advance to the next projection image stored in the folder. Continue applying the same ROI for the platform to the next projection image by selecting the ROI stored in the ROI manager and by confirming this ROI in the define the platform window. Before proceeding to the next projection image, make sure that the platform did not move during the experiment.

If the position of the platform did move, left click in the center of the selection and drag it into the required position. If the selection box does not match with the platform, left click outside of the selection and delineate a new selection for the platform using the polygon tool. Add this new selection to the ROI manager.

Then, verify the new selection by clicking okay in the define platform window, and continue the procedure until all images have properly defined platforms. The final task before processing the data is to define the minimum size for a fly. This is explained in the text protocol.

To quantify the flies escaping from the platform, first, set the minimum fly size. Then, indicate the largest number of flies in a file within the experimental series. Start the analyze function, and at the prompt, select the main directory for the experiment.

After running the macro, note that a new results file and a new image stack appeared in each folder. Open these files to ensure that the procedure worked correctly. Start the R or RStudio software package and open the Island Assay analysis script to process all the experiments simultaneously.

The script must be edited correctly for the analysis to succeed. Into the script at row 16, insert the path to the main directory that contains the experiments to be analyzed. Insert the path to the folder where the analysis output files should be stored into row 19.

The latter must be a location different from the directory containing the image data to be analyzed. Now, run the script from the toolbar and proceed with analyzing the results. The script Island Assay analysis exports a line graph for each experimental condition.

The graph shows the percentage of flies remaining on the platform over time for each replicate of that condition. The exported line graph, escape response:all conditions, summarizes the average and standard error of the mean flight escape response for the first 12 experimental conditions present in the main folder. The area under the curve for each experimental replicate is calculated to determine whether the experimental conditions differ significantly from each other.

The area under the curve and median value for each experimental condition is exported as a graph. Depending on the number of conditions present in the main folder, the script will perform either a two-tailed unpaired Welch T-test for two conditions or an anova with two key correction for more than two conditions. All numeric data calculated by the script Island Assay analysis is also exported and saved as csv or txt files in the data output folder.

Ataxia telangiectasia is an autosomal recessive movement disorder caused by mutations in the ATM gene. The disease is characterized by early onset of cerebellar ataxia. The effect of ubiquitously knocking down the fly ortholog of ATM was examined in the Island Assay and compared to controls.

Overall, ubiquitous knock-down of the fly ATM ortholog, Tefu, significantly decreased locomotor performance in the Island Assay compared to genetic background controls. Manual analysis of the recorded Island Assay data gave the same result as the automated analysis. After watching this video, you should have a good understanding in how to perform the Island Assay, how to run the Drosophila Island Assay macro, and how to operate the Island Assay analysis script.

While attempting this protocol, it's important to remember that the quality of the image segmentation is correlated with the quality of the movies. When better the contrast, the smoother the analysis. After its development, this technique paves the way for researchers to explore locomotor ability in Drosophila in high throughput.

After using this assay, other assays, such as those that test negative geotaxis can be used to further investigate locomotor defects.