The iFly tracking system for an automated locomotor and behavioural analysis of Drosophila melanogaster

Abstract

The use of animal models in medical research provides insights into molecular and cellular mechanisms of human disease, and helps identify and test novel therapeutic strategies. Drosophila melanogaster--the common fruit fly--is one of the most well-established model organisms, as its study can be performed more readily and with far less expense than for other model animal systems, such as mice, fish, or primates. In the case of fruit flies, standard assays are based on the analysis of longevity and basic locomotor functions. Here we present the iFly tracking system, which enables to increase the amount of quantitative information that can be extracted from these studies, and to reduce significantly the duration and costs associated with them. The iFly system uses a single camera to simultaneously track the trajectories of up to 20 individual flies with about 100 μm spatial and 33 ms temporal resolution. The statistical analysis of fly movements recorded with such accuracy makes it possible to perform a rapid and fully automated quantitative analysis of locomotor changes in response to a range of different stimuli. We anticipate that the iFly method will reduce very considerably the costs and the duration of the testing of genetic and pharmacological interventions in Drosophila models, including an earlier detection of behavioural changes and a large increase in throughput compared to current longevity and locomotor assays.

Figure 1. Scheme of the iFly apparatus.

(a) Scheme of the fly chamber with test tube, camera, and mirrors placed at angle δ; the three perspectives (I, II, and III) are projected onto the camera lens. (b) Image of fly chamber, showing how a test tube with flies can be inserted through a hole in the frosted plastic lid. (c) Snapshot from the graphical user interface (GUI) showing live video stream. The GUI contains components that allow the user to adjust parameters for the iFly chamber, camera, and image segmentation algorithm. (d) Example of a captured frame with results from the image segmentation algorithm overlaid; trajectories (black lines) and current fly positions (green circles and blue corners), from which the Cartesian coordinates of the trajectories of the flies are extracted, are shown, together with red lines that connect fly images predicted to be projections originating from the same fly. (e) Real-time three-dimensional reconstruction of the ray tracing calculations for visual control during image analysis. Images reflected by two mirrors are triangulated with the direct image to accurately locate the flies in the tube; camera (black box), tube (blue cylinder), mirrors, and fly positions (black dots) are shown, with direct rays drawn in blue, and those reflected on mirrors in red.

Figure 2. Demonstration of the spatial resolution of the iFly method.

Trajectories are from healthy flies at day 1 after hatching and reconstructed from fly locations determined by the iFly software over a short 7.5s video segment. The fly tube has a radius of 10mm with flies traveling up to 55mm vertically. A section is magnified to provide a close-up on various intersecting fly trajectories. Velocity vectors indicate direction and amplitude of fly locomotion. Fly locations are shown as small colored dots indicating clear separation and a sub-millimeter spatial resolution. For comparison, the length of a fly body is approximately 1.5-2mm.

Figure 3. Change in distribution of fly velocities over time.

The six panels show velocity distributions for 10 flies in a test tube at different stages of their lives. At each measurement, the test tube was dropped three times during continuous video capture followed by analysis of the first 15s of each of the three segments for a total of 45s. Velocities were assigned to bins of width 3mm/s with the first bin starting at 0mm/s. A decline in motility in flies is quantitatively expressed by a progressive left shift of the distributions and a decline in the mean velocity. Error bars indicate the bin-wise standard deviation over three replicas of 10 flies each.