Quantitative imaging of sleep behavior in Caenorhabditis elegans and larval Drosophila melanogaster
Quantitative imaging of sleep behavior in Caenorhabditis elegans and larval Drosophila melanogaster
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DOI：
10.1038/s41596-019-0146-6
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发表时间：
2019-05-01
期刊：
影响因子：
14.8
通讯作者：
Kayser, Matthew S.
中科院分区：
文献类型：
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作者：
Churgin, Matthew A.;Szuperak, Milan;Kayser, Matthew S.
睡眠在动物中几乎是普遍存在的，但人们对此仍知之甚少。最近的工作利用简单的模式生物，如秀丽线虫和黑腹果蝇幼虫，来研究睡眠的遗传和神经基础。然而，在这些系统中记录睡眠行为的手动方法是劳动密集型的，并且吞吐量低。为了解决这些局限性，我们开发了在定制的微制多孔底物中培养的单个动物的定量成像方法，并用它们来阐明睡眠的分子机制。在这里，我们描述了设计、生产和成像这些板所需的步骤，以及分析产生的行为数据。我们还描述了实验性地操纵睡眠的方法。按照这些步骤，经过类似2小时的实验准备，我们能够同时以10和27微米的空间分辨率对24只线虫从2龄幼虫到成虫或20只果蝇幼虫在2龄生活期进行成像。虽然这个系统已经被优化用于测量线虫幼虫和成虫以及果蝇幼虫的活动和静止，但它也可以用于评估其他短期或长期的行为。此外，只要稍加修改，它就可以适用于对各种小动物的行为监测。
Sleep is nearly universal among animals, yet remains poorly understood. Recent work has leveraged simple model organisms, such as Caenorhabditis elegans and Drosophila melanogaster larvae, to investigate the genetic and neural bases of sleep. However, manual methods of recording sleep behavior in these systems are labor intensive and low in throughput. To address these limitations, we developed methods for quantitative imaging of individual animals cultivated in custom microfabricated multiwell substrates, and used them to elucidate molecular mechanisms underlying sleep. Here, we describe the steps necessary to design, produce, and image these plates, as well as analyze the resulting behavioral data. We also describe approaches for experimentally manipulating sleep. Following these procedures, after similar to 2 h of experimental preparation, we are able to simultaneously image 24 C. elegans from the second larval stage to adult stages or 20 Drosophila larvae during the second instar life stage at a spatial resolution of 10 or 27 mu m, respectively. Although this system has been optimized to measure activity and quiescence in Caenorhabditis larvae and adults and in Drosophila larvae, it can also be used to assess other behaviors over short or long periods. Moreover, with minor modifications, it can be adapted for the behavioral monitoring of a wide range of small animals.