Revel Maxime, Nagoshi Emi, Maeda Robert
Department of Genetics and Development, University of Geneva, Geneva, Switzerland.
R Soc Open Sci. 2025 Sep 4;12(9):250764. doi: 10.1098/rsos.250764. eCollection 2025 Sep.
has been a pioneering model system for investigations into the genetic bases of behaviour. Studies of circadian activity were some of the first behaviours investigated in flies. The Activity Monitoring (DAM) system by TriKinetics played a key role in establishing the fundamental feedback loop of the circadian clock. Although this method has many times proven to be extremely useful, it suffers from its simplification of activity to the interruption of an infrared (IR) beam. It is blind to fly movements not disrupting the beam and any modifications to this assay to achieve better resolution often requires the purchase of new and expensive modules. We required a relatively high-throughput system to explore the potential post-mating activity changes of larger species. Rather than investing in a larger and more complex DAM system, we designed a new monitoring system that is more versatile, economic and sensitive than DAM. This new system, called DrosoVAM ( Video-assisted Activity Monitoring), is simple to implement and cost efficient, using a Raspberry Pi-controlled IR, digital video system to record multiple chambers and Python scripts that drive the deep learning software DeepLabCut, to track fly activity over multiple days.
果蝇一直是研究行为遗传基础的先驱模型系统。昼夜活动研究是最早在果蝇中进行研究的一些行为。TriKinetics公司的活动监测（DAM）系统在建立生物钟的基本反馈回路中发挥了关键作用。尽管这种方法多次被证明极其有用，但它将活动简化为对红外（IR）光束的中断。它对不干扰光束的果蝇运动视而不见，并且为了获得更好的分辨率而对该检测方法进行的任何修改通常都需要购买新的昂贵模块。我们需要一个相对高通量的系统来探索较大果蝇物种交配后潜在的活动变化。我们没有投资购买更大、更复杂的DAM系统，而是设计了一种新的监测系统，它比DAM系统更通用、经济且灵敏。这个新系统称为DrosoVAM（视频辅助活动监测），易于实施且成本效益高，它使用树莓派控制的红外数字视频系统来记录多个实验箱，并使用驱动深度学习软件DeepLabCut的Python脚本，来跟踪果蝇多天的活动。
