Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA.
Nat Methods. 2011 Jun 5;8(7):592-8. doi: 10.1038/nmeth.1625.
We designed a real-time computer vision system, the Multi-Worm Tracker (MWT), which can simultaneously quantify the behavior of dozens of Caenorhabditis elegans on a Petri plate at video rates. We examined three traditional behavioral paradigms using this system: spontaneous movement on food, where the behavior changes over tens of minutes; chemotaxis, where turning events must be detected accurately to determine strategy; and habituation of response to tap, where the response is stochastic and changes over time. In each case, manual analysis or automated single-worm tracking would be tedious and time-consuming, but the MWT system allowed rapid quantification of behavior with minimal human effort. Thus, this system will enable large-scale forward and reverse genetic screens for complex behaviors.
我们设计了一个实时计算机视觉系统,即多虫追踪器(MWT),它可以以视频速度同时定量分析在培养皿上的数十只秀丽隐杆线虫的行为。我们使用该系统研究了三种传统行为范式:在食物上的自发运动,其中行为在数十分钟内发生变化;化学趋向性,其中必须准确检测转向事件以确定策略;以及对敲击的反应习惯化,其中反应是随机的并且随时间变化。在每种情况下,手动分析或自动单虫追踪都将是繁琐和耗时的,但 MWT 系统允许以最小的人工努力快速量化行为。因此,该系统将能够进行大规模的正向和反向遗传筛选,以研究复杂行为。