A high-throughput system for quantifying the locomotion and social behavior of flies
The Fly Bowl behavior quantification system
We have developed a high-throughput system for quantifying the locomotion and social behavior of flies with both breadth and depth. This system was developed as part of the Fly Olympiad project at Janelia. We screened the behavioral effects of TrpA neural activation at a rate of 75 GAL4 lines per week over a period of 1.5 years.
In our system, we record video of groups of flies freely behaving in an open-field walking arena, the Fly Bowl. The Fly Bowl is a chamber for observing the locomotion and social behaviors of multiple flies. Its main difference from more standard arenas is that it was designed with automated tracking and behavior analysis algorithms in mind. We have made significant modifications to the original design to increase throughput, consistency, and image quality. These modifications allow us to use Ctrax to track individual flies’ positions accurately in a completely automated way. Our system consists of 8 bowls that we record from simultaneously.
To reduce disk storage, we developed a MATLAB-based data capture system which compresses our videos by a factor of 80 during recording and is lossless for the tracking algorithm (in our screen, we capture 11 TB of raw video data per week). Our data capture system also captures and monitors metadata information about the environment and the preparation of the flies to ensure that results are repeatable and data are comparable over long periods of time across the different rigs.
To provide oversight for collection of this large data set, we developed visualization tools for examining the stability of experimental conditions and behavior statistics over time, and ensuring that we understood and accounted for correlations between recorded metadata and behavior.
To analyze the data, we developed an automatic pipeline that uses the cluster at Janelia. Typically, data are analyzed within 24-hours of being collected and the results are stored in a database. The first step in our analysis is to track the positions of individual flies using an updated version of Ctrax. From the trajectories, we compute 85 time series of “per-frame” behavior measurements, for instance the fly’s speed in each frame, or the distance from the fly to the closest other fly in each frame. Our first level of characterization of the behavior of the flies are statistics of these measurements, in these examples, the average speed and the average distance to the closest fly, or histograms of these values.
Next, we use behavior classifiers trained using JAABA to compute discrete behavior labels for each fly and frame, labels of whether the fly is or is not performing each of a suite of behaviors, e.g. walking, chasing, and wing grooming. We can then represent the behavior of the flies in terms of the fraction of time that they perform a given behavior. We can also use these discrete behavior categories to segment the trajectories into similar types of data that can be analyzed together. Then, we can look at statistics of our per-frame measurements within these segments, e.g. average speed while chasing, or distance to the closest fly at the beginning of a jump. This allows us to remove the effects of common behaviors such as walking and stopping when scrutinizing less common but highly stereotyped behaviors such as courtship and grooming.
Fly Bowl Neural Activation Screen
As part of the Fly Olympiad team project at Janelia, we performed a high-throughput, large-scale activation screen of 2,200 transgenic lines of adult Drosophila from the Rubin GAL4 collection. For each of these lines of flies, a different sparse subset of neurons express the temperature sensitive TRPA1 neural effector using the the GAL4-UAS system. When the flies are at an elevated temperature, this sparse subset of neurons are activated. Our goal in the Fly Bowl screen is to understand how exciting these neurons affects behavior. More specifically, for each line, we are producing a quantitative description of how the behavior of flies from this line differs from the behavior of flies from a genetic control. These GAL4 lines are widely used at Janelia and elsewhere, and the behavior annotation provided by our screen will be a useful initial behavioral characterization in many studies.
In addition, the FlyLight team project at Janelia has imaged the dissected nervous systems of flies from each of these GAL4 lines to determine the expression pattern. Using the Fly Bowl screen data and the FlyLight data, we are performing a meta-analysis to determine which brain regions and neural circuits are involved in what behaviors. This analysis has the potential to provide insight into the organization of the fly brain and the function of individual neurons and anatomical regions.
We have screened a total of 2,200 lines. For 70% of these lines, data was collected on at least 2 separate occasions (different crosses at different times of year). Each time a line was tested, we collected 4 videos of 10 male and 10 female flies for 1,000 seconds each. In addition, we collected videos of our control flies multiple times per day. We reliably screened at a rate of 75 GAL4 lines per week over a 1.5 year period. In total, we collected, tracked, and analyzed 225 days of video of a total of 380,000 flies. This data set has been curated using a set of automatic checks to look for errors during collection or processing. We thus have a large, interesting, high quality data set to mine.
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