A portable system for monitoring the behavioral activity of Drosophila

Tracking the flight and landing behaviour of western flower thrips in response to single and two-colour cues

Real-time 3D tracking and high-speed videography was used to examine the behaviour of a worldwide greenhouse pest, the western flower thrips (WFT), in response to different colours in the context of improving trap design. Measurements were taken of the number of landings on, and flight activity near, a lamp containing two LEDs of either the same colour or a combination of two colours presented side by side. Main findings show that landing patterns of WFT are different between colours, with landings on UV(+ red) as highly attractive stimulus being mostly distributed at the bottom half of the lamp, while for yellow also as very attractive and green as a 'neutral' stimulus, landings were clearly on the upper rim of the lamp. Additionally, a positive interaction with the UV-A(+ red) and yellow combination elicited the highest number of landings and flight time in front of the LED lamp. Conversely, a negative interaction was observed with decreased landings and flight time found for yellow when blue was present as the adjacent colour. Overall, differences between treatments were less obvious for flight times compared to number of landings, with tracking data suggesting that WFT might use different colours to orientate at different distances as they approach a visual stimulus.

Artificial gravity partially protects space-induced neurological deficits in Drosophila melanogaster

Spaceflight poses risks to the central nervous system (CNS), and understanding neurological responses is important for future missions. We report CNS changes in Drosophila aboard the International Space Station in response to spaceflight microgravity (SFμg) and artificially simulated Earth gravity (SF1g) via inflight centrifugation as a countermeasure. While inflight behavioral analyses of SFμg exhibit increased activity, postflight analysis displays significant climbing defects, highlighting the sensitivity of behavior to altered gravity. Multi-omics analysis shows alterations in metabolic, oxidative stress and synaptic transmission pathways in both SFμg and SF1g; however, neurological changes immediately postflight, including neuronal loss, glial cell count alterations, oxidative damage, and apoptosis, are seen only in SFμg. Additionally, progressive neuronal loss and a glial phenotype in SF1g and SFμg brains, with pronounced phenotypes in SFμg, are seen upon acclimation to Earth conditions. Overall, our results indicate that artificial gravity partially protects the CNS from the adverse effects of spaceflight.

Automated real-time quantification of group locomotor activity in Drosophila melanogaster

Recent advances in neurogenetics have highlighted Drosophila melanogaster as an exciting model to study neural circuit dynamics and complex behavior. Automated tracking methods have facilitated the study of complex behaviors via high throughput behavioral screening. Here we describe a newly developed low-cost assay capable of real-time monitoring and quantifying Drosophila group activity. This platform offers reliable real-time quantification with open source software and a user-friendly interface for data acquisition and analysis. We demonstrate the utility of this platform by characterizing ethanol-induced locomotor activity in a dose-dependent manner as well as the effects of thermo and optogenetic manipulation of ellipsoid body neurons important for ethanol-induced locomotor activity. As expected, low doses of ethanol induced an initial startle and slow ramping of group activity, whereas high doses of ethanol induced sustained group activity followed by sedation. Advanced offline processing revealed discrete behavioral features characteristic of intoxication. Thermogenetic inactivation of ellipsoid body ring neurons reduced group activity whereas optogenetic activation increased activity. Together, these data establish the fly Group Activity Monitor (flyGrAM) platform as a robust means of obtaining an online read out of group activity in response to manipulations to the environment or neural activity, with an opportunity for more advanced post-processing offline.

The Role of AChE in Swimming Behavior of Daphnia magna: Correlation Analysis of Both Parameters Affected by Deltamethrin and Methomyl Exposure

The unpredictable toxicity of insecticides may cause behavior disorder of biological organisms. In order to assess the role of acetylcholinesterase (AChE) in swimming behavior of Daphnia magna, a correlation analysis of both parameters in 24 h exposure of deltamethrin (DM) and methomyl (MT) was investigated. The behavior responses of D. magna in DM (13.36 μg/L and 33.40 μg/L) and MT (19.66 μg/L and 49.15 μg/L) suggested that recovery behavior in the adjustment phase was crucial, and behavior homeostasis provided them with an optimal way to achieve a wider tolerance against environmental stress. During the experiment, positive effects on AChE activity occurred in the beginning of the exposure. Even though the de novo synthesis of AChE in D. magna might help it recover, the AChE inhibition in different treatments could be observed. Some induction effects on AChE activity at the beginning of exposure occurred, and a 50% decrease may cause toxic effects on behavior. In most treatments, the results showed that both behavior strength and AChE activity stayed in the same field within a correlation circle. These results illustrated that the environmental stress caused by both DM and MT could inhibit AChE activity and subsequently induce a stepwise behavior response, though both pesticides affect it as direct and indirect inhibitors, respectively.

Estimating Orientation of Flying Fruit Flies

The recently growing interest in studying flight behaviours of fruit flies, Drosophila melanogaster, has highlighted the need for developing tools that acquire quantitative motion data. Despite recent advance of video tracking systems, acquiring a flying fly’s orientation remains a challenge for these tools. In this paper, we present a novel method for estimating individual flying fly’s orientation using image cues. Thanks to the line reconstruction algorithm in computer vision field, this work can thereby focus on the practical detail of implementation and evaluation of the orientation estimation algorithm. The orientation estimation algorithm can be incorporated into tracking algorithms. We rigorously evaluated the effectiveness and accuracy of the proposed algorithm by running experiments both on simulation data and on real-world data. This work complements methods for studying the fruit fly’s flight behaviours in a three-dimensional environment.

Determination of the spontaneous locomotor activity in Drosophila melanogaster

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such behavior is spontaneous locomotor activity. Here we describe our protocol that utilizes Drosophila population monitors and a tracking system that allows continuous monitoring of the spontaneous locomotor activity of flies for several days at a time. This method is simple, reliable, and objective and can be used to examine the effects of aging, sex, changes in caloric content of food, addition of drugs, or genetic manipulations that mimic human diseases.

Three-dimensional tracking and behaviour monitoring of multiple fruit flies

The increasing interest in the investigation of social behaviours of a group of animals has heightened the need for developing tools that provide robust quantitative data. Drosophila melanogaster has emerged as an attractive model for behavioural analysis; however, there are still limited ways to monitor fly behaviour in a quantitative manner. To study social behaviour of a group of flies, acquiring the position of each individual over time is crucial. There are several studies that have tried to solve this problem and make this data acquisition automated. However, none of these studies has addressed the problem of keeping track of flies for a long period of time in three-dimensional space. Recently, we have developed an approach that enables us to detect and keep track of multiple flies in a three-dimensional arena for a long period of time, using multiple synchronized and calibrated cameras. After detecting flies in each view, correspondence between views is established using a novel approach we call the 'sequential Hungarian algorithm'. Subsequently, the three-dimensional positions of flies in space are reconstructed. We use the Hungarian algorithm and Kalman filter together for data association and tracking. We evaluated rigorously the system's performance for tracking and behaviour detection in multiple experiments, using from one to seven flies. Overall, this system presents a powerful new method for studying complex social interactions in a three-dimensional environment.