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斑马鱼幼体的自动化高通量行为分析

Automated high-throughput behavioral analyses in zebrafish larvae.

作者信息

Richendrfer Holly, Créton Robbert

机构信息

Department of Molecular Biology, Cell Biology and Biochemistry, Brown University.

出版信息

J Vis Exp. 2013 Jul 4(77):e50622. doi: 10.3791/50622.

Abstract

We have created a novel high-throughput imaging system for the analysis of behavior in 7-day-old zebrafish larvae in multi-lane plates. This system measures spontaneous behaviors and the response to an aversive stimulus, which is shown to the larvae via a PowerPoint presentation. The recorded images are analyzed with an ImageJ macro, which automatically splits the color channels, subtracts the background, and applies a threshold to identify individual larvae placement in the lanes. We can then import the coordinates into an Excel sheet to quantify swim speed, preference for edge or side of the lane, resting behavior, thigmotaxis, distance between larvae, and avoidance behavior. Subtle changes in behavior are easily detected using our system, making it useful for behavioral analyses after exposure to environmental toxicants or pharmaceuticals.

摘要

我们创建了一种新型高通量成像系统,用于分析多通道培养板中7日龄斑马鱼幼虫的行为。该系统测量自发行为以及对厌恶刺激的反应,通过PowerPoint演示文稿向幼虫展示该刺激。使用ImageJ宏对记录的图像进行分析,该宏会自动分离颜色通道、减去背景并应用阈值来识别各幼虫在通道中的位置。然后,我们可以将坐标导入Excel工作表,以量化游泳速度、对通道边缘或侧边的偏好、静止行为、趋触性、幼虫之间的距离以及回避行为。使用我们的系统可以轻松检测到行为的细微变化,这使其在暴露于环境毒物或药物后进行行为分析时非常有用。

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