Vannoni Elisabetta, Voikar Vootele, Colacicco Giovanni, Sánchez María Alvarez, Lipp Hans-Peter, Wolfer David P
Institute of Anatomy, University of Zürich, Switzerland.
Neuroscience Center, University of Helsinki, Finland.
J Neurosci Methods. 2014 Aug 30;234:26-37. doi: 10.1016/j.jneumeth.2014.04.026. Epub 2014 May 1.
Modern molecular genetics create a rapidly growing number of mutant mouse lines, many of which need to be phenotyped behaviorally. Poor reliability and low efficiency of traditional behavioral tests have prompted the development of new approaches to behavioral phenotyping, such as fully automated analysis of behavior in the homecage.
We asked whether the analysis of spontaneous behavior during the first week in the social homecage system IntelliCage could provide useful prescreening information before specialized and time consuming test batteries are run. To determine how much behavioral variation is captured in this data, we performed principal component analysis on free adaptation data of 1552 mice tested in the IntelliCage during the past years. We then computed individual component scores to characterize and compare groups of mice.
We found 11 uncorrelated components which accounted for 82% of total variance. They characterize frequency and properties of corner visits and nosepokes, drinking activity, spatial distribution, as well as diurnal time course of activity. Behavioral profiles created using individual component scores were highly characteristic for different inbred strains or different lesion models of the nervous system. They were also remarkably stable across labs and experiments.
Monitoring of mutant mice with known deficits in hippocampus-dependent tests produced profiles very similar to those of hippocampally lesioned mice.
Taken together, our results suggest that already the monitoring of spontaneous behavior during a week of free adaptation in the IntelliCage can contribute significantly to high throughput prescreening of mutant mice.
现代分子遗传学产生了数量迅速增长的突变小鼠品系,其中许多需要进行行为表型分析。传统行为测试的可靠性差和效率低促使了行为表型分析新方法的发展,例如对笼内行为进行全自动分析。
我们探讨了在社交笼养系统IntelliCage中对小鼠第一周的自发行为进行分析,是否能在进行专门且耗时的测试组合之前提供有用的预筛选信息。为了确定该数据能捕捉到多少行为变异,我们对过去几年在IntelliCage中测试的1552只小鼠的自由适应数据进行了主成分分析。然后我们计算个体成分得分来表征和比较小鼠组。
我们发现了11个不相关的成分,它们占总方差的82%。它们表征了角落访问和鼻触的频率及特性、饮水活动、空间分布以及活动的昼夜时间进程。使用个体成分得分创建的行为概况对于不同的近交系或不同的神经系统损伤模型具有高度特征性。它们在不同实验室和实验中也非常稳定。
对在依赖海马体的测试中存在已知缺陷的突变小鼠进行监测,得到的概况与海马体损伤小鼠的概况非常相似。
综上所述,我们的结果表明,在IntelliCage中对一周自由适应期间的自发行为进行监测,就能对突变小鼠的高通量预筛选做出显著贡献。