Assessing mouse behaviour throughout the light/dark cycle using automated in-cage analysis tools.

Assessing mouse behaviour throughout the light/dark cycle using automated in-cage analysis tools.
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DOI:
10.1016/j.jneumeth.2017.04.014
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发表时间:
2018-04-15
影响因子:
3
通讯作者:
Nolan PM
Nolan PM
中科院分区:
医学4区
文献类型:
--
作者:
Bains RS;Wells S;Sillito RR;Armstrong JD;Cater HL;Banks G;Nolan PM

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自动评估小鼠的笼舍行为是稳健和可靠的。对多个光/暗周期的分析提高了对行为进行分类的能力。结合RFID和视频分析,可以对分组饲养的动物进行饲养笼分析。降低小鼠试验结果变异性的一个重要因素是开发可用于连续自动化饲养笼评估的测定。我们的经验表明,这一点在小鼠轮跑活动的长期评估中得到了最明显的证明。历史上,小鼠和其他啮齿动物的轮跑已被用作一种可靠的测定方法,以精确测定小鼠昼夜节律的固有周期。此外,该测定在解剖哺乳动物昼夜节律的分子遗传基础方面也是有用的。在梳理出这个测试的元素,确定其鲁棒性-自动评估长时间间隔内的非强迫行为在家里的笼子里-我们和其他人一直在研究是否可以使用类似的测试设备来准确区分不同的行为参数在小鼠的差异。首先,使用这些系统,我们探索了一些小鼠近交系的行为,以确定我们是否可以提取生物学上有意义的差异。其次,我们测试了一些相关的突变株系,以确定如何区分这些参数。我们的研究结果表明,与传统的笼外表型相比,可以通过在一个或多个光:暗周期内监测家庭笼中的行为来建立对小鼠突变表型的更深入的理解。
Automated assessment of mouse home-cage behaviour is robust and reliable. Analysis over multiple light/dark cycles improves ability to classify behaviours. Combined RFID and video analysis enables home-cage analysis in group housed animals. An important factor in reducing variability in mouse test outcomes has been to develop assays that can be used for continuous automated home cage assessment. Our experience has shown that this has been most evidenced in long-term assessment of wheel-running activity in mice. Historically, wheel-running in mice and other rodents have been used as a robust assay to determine, with precision, the inherent period of circadian rhythms in mice. Furthermore, this assay has been instrumental in dissecting the molecular genetic basis of mammalian circadian rhythms. In teasing out the elements of this test that have determined its robustness – automated assessment of an unforced behaviour in the home cage over long time intervals – we and others have been investigating whether similar test apparatus could be used to accurately discriminate differences in distinct behavioural parameters in mice. Firstly, using these systems, we explored behaviours in a number of mouse inbred strains to determine whether we could extract biologically meaningful differences. Secondly, we tested a number of relevant mutant lines to determine how discriminative these parameters were. Our findings show that, when compared to conventional out-of-cage phenotyping, a far deeper understanding of mouse mutant phenotype can be established by monitoring behaviour in the home cage over one or more light:dark cycles.
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