A Simple Technique to Assay Locomotor Activity in Drosophila
February 24th, 2023
The present protocol assesses the locomotor activity of Drosophila by tracking and analyzing the movement of flies in a hand-made arena using open-source software Fiji, compatible with plugins to segment pixels of each frame based on high-definition video recording to calculate parameters of speed, distance, etc.
The method is based on open source software to systematically evaluate the local motor activities for the tracking behavior of adult and the larvae flies from recorded video. This method requires low cost device integration to record and analyze behavior, making it an affordable and effective approach for screening fly locomotion. This technology is employed to identify behavioral modification in a fly model of human disease with local motion impairment, but it is not suitable for treating disease, disabilities, or difficulties.
It is essential to clear the relevant video window during the analysis process, namely the original and the processing video window. To begin, mix reagent A and reagent B of the silica kit at a ratio of one to 10, according to the manufacturer's instructions, to prepare the open field arena for drosophila locomotion tracking. Next, set the HD camera on a tripod, adjusting it so that the camera lens is perpendicular to the surface of the silica arena.
Then open the video with Fiji. Drag the progress bar to the initial frame and tacitly approve. Choose the whole body of the fly using the freehand selection tool.
Click on image, adjust, and brightness and contrast to adjust the white balance until the gray value of the selected area approaches the broad background. Transfer the anesthetized fly to the open field arena. Once the fly recovers from the anesthesia, put the arena dish with the fly under the camera and shake it quickly from side to side to ensure the fly is in motion when the recording begins.
Press the record button on the camera application to start video recording. Upon completion of the recording, press the stop button to terminate the video recording. Convert the recorded videos into AVI format with M-J pagan coding so they can be opened and analyzed using Fiji.
Also set the frames per second of the video to 15 fps for adult flies and 12 fps for larvae. To open the video with Fiji, select the two options, use virtual stack and convert to gray scale, in the pop-up window. Obtain a processing window by using the set active image tool of the animal tracker plugin, and create a tracking area that circles the arena in the original video window, using the oval tool.
Set the filters and the parameters of the two filters for the first blank frame in the processing window. Then select the next frame in the original video window, and choose the filtered surface of the processing window. Once a filtered processing window is selected, use the set threshold tool to turn the tract fly with a red profile, covered in the processing window.
Then use the set blob detector to let the computer recognize the fly with a red profile, covered in the processing window. Set the last frame for the adult fly or larvae, as described in the text manuscript. Use the show blobs tool to present a tracking rectangle in the original video window.
Start the tracking and export the tracking file after the monitoring is completed. Load the track and zone files using the animal tracker and tracking analyzer plugin. Select the desired index using zone settings, and alter the parameter settings.
Calculate the time of the frame interval using the frame rate. Produce the quantitative analysis charts using spreadsheet software and graph pad prism, after being analyzed in the tracking analyzer. Open the track file.
Copy all coordinates to Microsoft Office Excel and split the cells using the space key. To calculate the immobility time per frame interval, select all calculated results and insert a column chart to visually exhibit the immobility time by the margin of the whole column chart. To illustrate the changes in the angle of direction, select all calculated results and insert a scatter diagram.
Adult flies and third Instar larvae, treated with Rotenone, had significant locomotor deficits compared to those of control flies, fed with solvent DMSO. Quantitative analysis of the Rotenone treatment in adult flies showed a significant decrease in the distance traveled and the mean velocity. And a significant increase in the immobility time.
Representative graphs showed fewer peaks for the movement speed per frame interval in flies fed with Rotenone compared to those in the control, indicating the severity of the locomotor activity deficit. The institution-istic immobility column of moved pixels per frame also showed significantly less movement within one minute for Rotenone fed flies, compared to the control flies. Representative graphs illustrating the moving angle of direction changes in Rotenone fed, and control animals also revealed alterations in the direction chosen by flies.
Similar results were observed for the third Instar larvae. The results revealed that the behavioral movement of tracking larvae fed with Rotenone was significantly impaired compared to the control. The most crucial step in the analysis process is forming the first of blank frame, as it evidence whether the software can check effectively.
This technology could allow researchers to delve deeper into the underlying mechanism of multiple defects, such as nerve or muscle injury.
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Overview
This protocol evaluates the locomotor activity of Drosophila by tracking their movement in a hand-made arena. Using open-source software Fiji, researchers can analyze high-definition video recordings to calculate parameters such as speed and distance.
Key Study Components
Area of Science
- Neuroscience
- Behavioral Analysis
- Genetics
Background
- The method allows for systematic evaluation of locomotor activities in adult and larval flies.
- It utilizes low-cost device integration for recording and analyzing behavior.
- This approach is effective for screening fly locomotion.
- It can identify behavioral modifications in fly models of human diseases.
Purpose of Study
- To assess locomotor activity in Drosophila.
- To provide an affordable method for behavioral analysis.
- To facilitate the study of locomotion impairment related to human diseases.
Methods Used
- Mixing reagents to prepare the open field arena for tracking.
- Setting up an HD camera to record fly movement.
- Using Fiji software to analyze recorded video.
- Ensuring the video window is clear during analysis.
Main Results
- Successful tracking of Drosophila locomotion.
- Quantitative analysis of speed and distance traveled.
- Identification of behavioral changes in response to experimental conditions.
- Demonstration of the method's effectiveness for low-cost behavioral screening.
Conclusions
- The method provides a reliable way to assess Drosophila locomotion.
- It is suitable for studying behavioral modifications linked to diseases.
- This approach can enhance understanding of locomotion impairments.
Frequently Asked Questions
Executive Industry Relevance
Quantitative behavioral assays in Drosophila enable early-stage de-risking of neurodegenerative and neuromuscular disease models by providing reproducible, scalable locomotor readouts. This open-source, video-based workflow supports high-throughput screening of genetic and pharmacological interventions, facilitating robust target validation and mechanistic interrogation. The approach enhances predictive confidence at the discovery-to-preclinical interface, supporting portfolio triage and translational continuity.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables systematic interrogation of motor function deficits in disease-relevant fly models.
- Supports functional validation of genetic or pharmacological targets impacting locomotion.
- Provides quantitative endpoints for mechanistic de-risking and hypothesis testing.
- Facilitates rapid triage of candidate interventions based on behavioral phenotypes.
Screening & Assay Development
- Delivers standardized, reproducible locomotor activity measurements for assay development.
- Supports scalable screening of transgenic and drug-treated flies using open-source analytics.
- Generates quantitative outputs (distance, velocity, immobility time) for reliable compound evaluation.
- Enables platform reuse across multiple behavioral paradigms and experimental cohorts.
Translational & Preclinical Research
- Aligns behavioral phenotypes in Drosophila with disease-relevant endpoints for translational studies.
- Provides continuity from early discovery through preclinical validation of neuroactive compounds.
- Supports risk-adjusted advancement decisions based on robust, quantitative behavioral data.
- Facilitates mechanistic exploration of neurodegenerative and neuromuscular disease pathways.
Pipeline & Workflow Integration
This method integrates into the discovery pipeline from early target validation through preclinical model assessment, supporting both genetic and pharmacological screening workflows.
- Discovery Biology: Enables hypothesis-driven testing of gene or compound effects on locomotor behavior.
- Screening: Provides reproducible, quantitative locomotor metrics for assay standardization and compound triage.
- Analytics: Outputs include distance traveled, mean velocity, immobility time, and directional changes for comparative analysis.
- Translational Research: Connects fly behavioral phenotypes to disease-relevant functional endpoints.
- Enterprise Reuse: Open-source, low-cost platform supports broad adoption across R&D teams and disease areas.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in early-stage models.
- Operational Value: Standardizes behavioral assays for reproducibility and scalability across studies.
- Strategic Value: Informs go/no-go decisions and enhances capital efficiency by enabling robust early de-risking.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of candidate targets and compounds.
Implementation Considerations
- Requires expertise in behavioral analysis and open-source image processing (Fiji, AnimalTracker).
- Needs high-definition video capture and compatible computational infrastructure.
- Demands cross-team standardization of arena preparation and video analysis parameters.
- Adaptable to both adult and larval Drosophila models with protocol adjustments.
- Dependent on careful frame selection and thresholding for accurate tracking and quantification.
