这项工作是支持由美国国立卫生研究院补助NIH34958一，E和NS061952 JC

<ol>
	<li>Brand, A. H., Perrimon, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+gene+expression+as+a+means+of+altering+cell+fates+and+generating+dominant+phenotypes.">Targeted gene expression as a means of altering cell fates and generating dominant phenotypes.</a> Development. 118, 401-415 (1993).</li><li>Chen, W. F., Low, K. H., Lim, C., Edery, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermosensitive+splicing+of+a+clock+gene+and+seasonal+adaptation.">Thermosensitive splicing of a clock gene and seasonal adaptation.</a> Cold Spring Harb Symp Quant Biol. 72, 599-606 (2007).</li><li>Chiu, J. C., Vanselow, J. T., Kramer, A., Edery, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+phospho-occupancy+of+an+atypical+SLIMB-binding+site+on+PERIOD+that+is+phosphorylated+by+DOUBLETIME+controls+the+pace+of+the+clock.">The phospho-occupancy of an atypical SLIMB-binding site on PERIOD that is phosphorylated by DOUBLETIME controls the pace of the clock.</a> Genes Dev. 22, 1758-1772 (2008).</li><li>Dubruille, R., Murad, A., Rosbash, M., Emery, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+constant+light-genetic+screen+identifies+KISMET+as+a+regulator+of+circadian+photoresponses.">A constant light-genetic screen identifies KISMET as a regulator of circadian photoresponses.</a> PLoS Genet. 12, e1000787-e1000787 (2009).</li><li>Glaser, F. T., Stanewsky, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temperature+synchronization+of+the+Drosophila+circadian+clock.">Temperature synchronization of the Drosophila circadian clock.</a> Curr Biol. 15, 1352-1363 (2005).</li><li>Helfrich-F&#246;rster, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+control+of+morning+and+evening+components+in+the+activity+rhythm+of+Drosophila+melanogaster-+sex-specific+differences+suggest+a+different+quality+of+activity.">Differential control of morning and evening components in the activity rhythm of Drosophila melanogaster- sex-specific differences suggest a different quality of activity.</a> J Biol Rhythms. 15, 135-154 (2000).</li><li>Hendricks, J. C., Finn, S. M., Pancleri, K. A., Chavkin, J., Williams, J., Sehgal, A., Pack, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rest+in+Drosophila+is+a+sleep-like+state.">Rest in Drosophila is a sleep-like state.</a> Neuron. 25, 129-138 (2000).</li><li>Ho, K. S., Sehgal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drosophila+melanogaster:+an+insect+model+for+fundamental+studies+of+sleep.">Drosophila melanogaster: an insect model for fundamental studies of sleep.</a> Methods Enzymol. 393, 772-793 (2005).</li><li>Koh, K., Evans, J. M., Hendricks, J. C., Sehgal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Drosophila+model+for+age-associated+changes+in+sleep:+wake+cycles.">A Drosophila model for age-associated changes in sleep: wake cycles.</a> Proc Natl Acad Sci USA. 103, 13843-13847 (2006).</li><li>Konopka, R. J., Benzer, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clock+mutants+of+Drosophila+melanogaster.">Clock mutants of Drosophila melanogaster.</a> Proc Natl Acad Sci USA. 68, 2112-2116 (1971).</li><li>McGuire, S. E., Roman, G., Davis, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+expression+systems+in+Drosophila:+a+synthesis+of+time+and+space.">Gene expression systems in Drosophila: a synthesis of time and space.</a> Trends Genet. 20, 384-391 (2004).</li><li>Osterwalder, T., Yoon, K. S., White, B. H., Keshishian, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+conditional+tissue-specific+transgene+expression+system+using+inducible+GAL4.">A conditional tissue-specific transgene expression system using inducible GAL4.</a> Proc Natl Acad Sci USA. 98, 12596-12601 (2001).</li><li>Rosato, E., Kyriacou, C. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+locomotor+activity+rhythms+in+Drosophila.">Analysis of locomotor activity rhythms in Drosophila.</a> Nature Protocols. 1, 559-568 (2006).</li><li>Sehadova, H., Glaser, F. T., Gentile, C., Simoni, A., Giesecke, A., Albert, J. T., Stanewsky, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temperature+entrainment+of+Drosophila's+circadian+clock+involves+the+gene+nocte+and+signaling+from+peripheral+sensory+tissues+to+the+brain.">Temperature entrainment of Drosophila's circadian clock involves the gene nocte and signaling from peripheral sensory tissues to the brain.</a> Neuron. 64, 251-266 (2009).</li><li>Zimmerman, J. E., Raizen, D. M., Maycock, M. H., Maislin, G., Pack, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+video+method+to+study+Drosophila+sleep.">A video method to study Drosophila sleep.</a> Sleep. 31, 1587-1598 (2008).</li><li>Zordan, M. A., Benna, C., Mazzotta, G., Rosato, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+and+analyzing+Drosophila+circadian+locomotor+activity.">Monitoring and analyzing Drosophila circadian locomotor activity.</a> In Circadian Rhythms Methods and Protocols. , (2007).</li></ol>

在这个协议中，我们描述了测量果蝇自发活动的节奏，一个可靠的输出时钟功能的标准读数蝇生物钟的行为的程序。这已用于检测新的时钟突变体（如Konopka和1971年本泽 ; Dubruille等2009）的大型屏幕，并不断地剖析和了解在体内的时钟功能。它也被用来研究果蝇的睡眠觉醒周期，尽管最近的报告表明，视频数字化分析是更可靠的量化的睡眠比使用自主活动的节奏（ 齐默尔曼等人，2008年） 。当使用自主活动的节奏来分析睡眠，在白天的睡眠比例往往被高估。 为了确保本议定书的成功和可重复性，它是至关重要的测定年龄，遗传背景相似的苍蝇，并在同等条件下饲养，水果中的行为表型的苍蝇，如昼夜节律和睡眠/休息活动是非常敏感所有这些因素。在一次实验中使用多个孵化器，重要的是要确保所有孵化器在预期的温度作为温度的函数，因为有些昼夜参数可能会改变。一个字谨慎考虑购买苍蝇孵化器时，并非所有的平等。虽然我们毫不犹豫地推荐任何特定的单位有很多的选择。在&lt;www.flybase.org&gt;提供一个很好的资源， 寻找果蝇工作的孵化器公司出售。有些公司甚至出售“ 果蝇生物钟”的孵化器，其中附加功能，如已为Trikinetics系统和温度斜坡（例如，Tritech）有线。重要功能包括周日光控的能力和良好的温度控制在对果蝇的生理范围（〜15-30 ℃）。孵化器的价格和大小有很大的差异，但是从Trikinetics新的活动监视器，即使是小规模的孵化器，可以容纳相当多的这些设备的数量。此外，虽然湿度控制的孵化器，可用于，这个新增的功能是没有必要的，只要你放在一个小泛水提供湿度（50-70％的罚款）。最后，虽然我们经常使用的数据分析，在本议定书FaasX和失眠，有替代方案和软件（2006年Rosato和Kyriacou），如ClockLab（ActiMetrics），布兰代斯节奏包（D.惠勒，医学院，休斯敦贝勒大学），MAZ（Zordan 等，2007）。

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		<div>
		<table border="1">
		<thead>
		<tr>
		<th>Material Name</th>
		<th>Type</th>
		<th>Company</th>
		<th>Catalogue Number</th>
		<th>Comment</th>
		</tr>
		</thead>
		<tbody>
		
<tr>
<td>Drosophila activity monitor (DAM)</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>DAM2 or DAM5</td>
<td>DAM2 monitors are more compact, and more can fit into a single incubator</td>
</tr>
<tr>
<td>Power supply interface unit (for DAM system)</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>PSIU9</td>
<td>Includes PS9-1 AC Power Supply</td>
</tr>
<tr>
<td>Light controller</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>LC6</td>
<td>&nbsp;</td>
<tr>
<td>Pyrex glass tubes</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>PGT5, PGT7, and PGT10</td>
<td>&nbsp;</td>
<tr>
<td>Plastic activity tube caps</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>CAP5</td>
<td>Yarn can be used instead of plastic caps.</td>
</tr>
<tr>
<td>DAM System data collection software</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>&nbsp;</td>
<td>Versions available for both Mac and PC</td>
</tr>
<tr>
<td>FaasX software</td>
<td>&nbsp;</td>
<td>M. Boudinot and F. Rouyer, Centre National de la Recherche Scientifique, Gif-sur-Yvette Cedex, France</td>
<td>&nbsp;</td>
<td>Only for Mac</td>
</tr>
<tr>
<td>Insomniac 2.0 software</td>
<td>&nbsp;</td>
<td>Leslie Ashmore, Department of Pharmacology &amp; Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA</td>
<td>&nbsp;</td>
<td>Runs on Matlab. Can be used on both PC and Macintosh.</td>
</tr>
<tr>
<td>Environmental incubator with temperature and diurnal control, e.g. Percival incubator</td>
<td>&nbsp;</td>
<td>Percival Scientific, Inc.</td>
<td>I-30BLL</td>
<td>Interior space dimension:
Width: 65cm;
Height: 86cm;
Depth: 55cm</td>
</tr>
<tr>
<td>Environmental incubator with temperature and diurnal control, e.g. DigiTherm Heating/Cooling Incubator with Circadian Timed Lighting and Timed Temperature</td>
<td>&nbsp;</td>
<td>Tritech Research, Inc.</td>
<td>05DT2CIRC001</td>
<td>Interior space dimension:
Width: 36m;
Height: 56m;
Depth: 28cm</td>
</tr>
<tr>
<td>APC Smart-UPS 2200VA 120V (Emergency power backup unit)</td>
<td>&nbsp;</td>
<td>APC</td>
<td>SU2200NET</td>
<td>Output Power Capacity of 1600 Watts</td>
</tr>
<tr>
<td>Sucrose</td>
<td>&nbsp;</td>
<td>Sigma</td>
<td>S7903</td>
<td>&nbsp;</td>
<tr>
<td>Bacto Agar</td>
<td>&nbsp;</td>
<td>Becton Dickinson</td>
<td>214010</td>
<td>&nbsp;</td>
<tr>
<td>TissuePrep Paraffin pellets</td>
<td>&nbsp;</td>
<td>Fisher Scientific</td>
<td>T565</td>
<td>Melting point 56&deg;C-57&deg;C</td>
</tr>
<tr>
<td>Block heater </td>
<td>&nbsp;</td>
<td>VWR</td>
<td>12621-014</td>
<td>&nbsp;</td>		</tbody>
		</table>
		</div>

assaying locomotor activity to study circadian rhythms and sleep parameters in drosophila

大多数生命形式表现出的细胞，生理和行为现象，是由内源性昼夜驱动（≡24小时）心脏起搏器或时钟的生活节奏。在人体生理系统的故障与许多疾病或功能紊乱。对我们的基本生理节律的机制认识出现了很大的进展，从遗传筛选，据此作为时钟功能读出一个容易测量的行为节奏。利用果蝇的研究，我们了解细胞和生化的昼夜节律的基地作出了开创性的贡献。在果蝇中读出测量的标准生物钟的行为是自发活动。在一般情况下，监控系统包括专门设计的设备，可以测量对果蝇的运动运动。这些设备被安置在环境控制的孵化器坐落在暗室和使用红外光束中断记录的小管内所载的个人苍蝇的自发活动。当过多少天计算， 果蝇表现出每天的活动和不活动周期，行为的节奏，是由动物的内源性昼夜节律系统管辖。与市售的自发活动的监控设备的出现和发展的数据分析软件方案，整个程序已经简化。我们使用系统的Trikinetics公司，这是这里所描述的过程，是目前全世界使用最流行的系统。最近，相同的监控设备已被用于研究在果蝇的睡眠行为。由于日常唤醒许多果蝇的睡眠周期可以同时测量只有1至2周，连续的自发活动数据通常是足够的，这个系统是理想的大型屏幕，以确定果蝇表现改变生物钟或睡眠属性。

Watch this Scientific Journal Video about Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila at JoVE.com

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

我们描述用于记录日常的自发活动节律的过程<em&gt;果蝇</em&gt;和随后的数据分析。自发活动节律是一个可靠的动物生物钟的行为输出，时钟功能的标准读数研究昼夜的突变体或环境研究如何调节昼夜节律系统时使用。

含量自发活动，研究昼夜节律和睡眠参数果蝇</em

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) ...

assaying-locomotor-activity-to-study-circadian-rhythms-sleep

Research

JoVE Journal

Neuroscience

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

46.2K 次观看.  Rutgers University. 我们描述用于记录日常的自发活动节律的过程果蝇和随后的数据分析。自发活动节律是一个可靠的动物生物钟的行为输出，时钟功能的标准读数研究昼夜的突变体或环境研究如何调节昼夜节律系统时使用。

视频: Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

Laser Capture Microdissection of Drosophila Peripheral Neurons

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the molecular mechanisms underlying class-specific dendrite morphogenesis1,2. To facilitate molecular analyses of class-specific da neuron development, it is vital to obtain these cells in a pure population. Although a range of different cell, and tissue-specific RNA isolation techniques exist for Drosophila cells, including magnetic bead based cell purification3,4, Fluorescent Activated Cell Sorting (FACS)5-8, and RNA binding protein based strategies9, none of these methods can be readily utilized for isolating single or multiple class-specific Drosophila da neurons with a high degree of spatial precision. Laser Capture Microdissection (LCM) has emerged as an extremely powerful tool that can be used to isolate specific cell types from tissue sections with a high degree of spatial resolution and accuracy. RNA obtained from isolated cells can then be used for analyses including qRT-PCR and microarray expression profiling within a given cell type10-16. To date, LCM has not been widely applied in the analysis of Drosophila tissues and cells17,18, including da neurons at the third instar larval stage of development. 
Here we present our optimized protocol for isolation of Drosophila da neurons using the infrared (IR) class of LCM. This method allows for the capture of single, class-specific or multiple da neurons with high specificity and spatial resolution. Age-matched third instar larvae expressing a UAS-mCD8::GFP19 transgene under the control of either the class IV da neuron specific ppk-GAL420 driver or the pan-da neuron specific 21-7-GAL421 driver were used for these experiments. RNA obtained from the isolated da neurons is of very high quality and can be directly used for downstream applications, including qRT-PCR or microarray analyses. Furthermore, this LCM protocol can be readily adapted to capture other Drosophila cell types a various stages of development dependent upon the cell type specific, GAL4-driven expression pattern of GFP.

Laser Capture Microdissection of Drosophila Peripheral Neurons

In this video-article we present a method for isolating single or multiple Drosophila da neurons from third instar larvae using the infrared capture (IR) class of Laser Capture Microdissection (LCM). RNA obtained from the isolated neurons can be readily used for downstream applications including qRT-PCR or microarray analyses.

激光捕获显微切割技术的果蝇外周神经元

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the ...

科研

神经科学

Measuring Circadian and Acute Light Responses in Mice using Wheel Running Activity

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2. They are responsible for timing our sleep/wake cycles and hormone secretion. Since this timing is not precisely 24-hours, it is synchronized to the solar day by light input. This is accomplished via photic input from the retina to the suprachiasmatic nucleus (SCN) which serves as the master pacemaker synchronizing peripheral clocks in other regions of the brain and peripheral tissues to the environmental light dark cycle3-7. The alignment of rhythms to this environmental light dark cycle organizes particular physiological events to the correct temporal niche, which is crucial for survival8. For example, mice sleep during the day and are active at night. This ability to consolidate activity to either the light or dark portion of the day is referred to as circadian photoentrainment and requires light input to the circadian clock9. Activity of mice at night is robust particularly in the presence of a running wheel. Measuring this behavior is a minimally invasive method that can be used to evaluate the functionality of the circadian system as well as light input to this system. Methods that will covered here are used to examine the circadian clock, light input to this system, as well as the direct influence of light on wheel running behavior.

This article will review methods that can be used to determine circadian function and light responsiveness in mice.

测量小鼠使用车轮运行活动的昼夜和急性对光反应

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2.  They ...

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of these diseases, including Alzheimer's, Parkinson's and Huntington's disease are characterized by age-dependent deterioration in learning and memory functions and movement coordination2. Here we use behavioral assays, including the negative geotaxis assay3 and the aversive phototaxic suppression assay (APS assay)4,5, to show that some of the behavior characteristics associated with human neurodegeneration can be recapitulated in flies. In the negative geotaxis assay, the natural tendency of flies to move against gravity when agitated is utilized to study genes or conditions that may hinder locomotor capacities. In the APS assay, the learning and memory functions are tested in positively-phototactic flies trained to associate light with aversive bitter taste and hence avoid this otherwise natural tendency to move toward light. Testing these trained flies 6 hours post-training is used to assess memory functions. Using these assays, the contribution of any genetic or environmental factors toward developing neurodegeneration can be easily studied in flies.

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Behavior assays for measuring locomotor functions, learning, and memory abilities in Drosophila.

含量的运动能力，学习和记忆的赤字果蝇</em神经退行性疾病>模型

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of ...

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of the breadth of molecular regulation. Newer approaches such as high-resolution RNA sequencing (RNA-Seq)1 provides new and expansive information about tissue- or state-specific expression such as relative transcript levels, alternative splicing, and micro RNAs2-4. Prospects for employing the RNA-Seq method in comparative whole transcriptome profiling5 within discrete tissues or between phenotypically distinct groups of individuals affords new avenues for elucidating molecular mechanisms involved in both normal and abnormal physiological states. Recently, whole transcriptome profiling has been performed on human brain tissue, identifying gene expression differences associated with disease progression6. However, the use of next-generation sequencing has yet to be more widely integrated into mammalian studies.
Gene expression studies in mouse models have reported distinct profiles within various brain nuclei using laser capture microscopy (LCM) for sample excision7,8. While LCM affords sample collection with single-cell and discrete brain region precision, the relatively low total RNA yields from the LCM approach can be prohibitive to RNA-Seq and other profiling approaches in mouse brain tissues and may require sub-optimal sample amplification steps. Here, a protocol is presented for microdissection and total RNA extraction from discrete mouse brain regions. Set-diameter tissue corers are used to isolate 13 tissues from 750-&mu;m serial coronal sections of an individual mouse brain. Tissue micropunch samples are immediately frozen and archived. Total RNA is obtained from the samples using magnetic bead-enabled total RNA isolation technology. Resulting RNA samples have adequate yield and quality for use in downstream expression profiling. This microdissection strategy provides a viable option to existing sample collection strategies for obtaining total RNA from discrete brain regions, opening possibilities for new gene expression discoveries.

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling  |

RNA expression profiling of discrete mouse brain regions requires a precise and repeatable tissue collection strategy. A protocol that uses both coronal brain sectioning and tissue corer-assisted microdissection is described here. The yield and quality of total RNA obtained from the resulting samples confirms the utility of the outlined method.

总RNA的分离和下游下一代测序和基因表达谱的非激光捕获显微切割离散小鼠脑地区显微镜方法

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of ...

Simultaneous Electroencephalography, Real-time Measurement of Lactate Concentration and Optogenetic Manipulation of Neuronal Activity in the Rodent Cerebral Cortex

Although the brain represents less than 5% of the body by mass, it utilizes approximately one quarter of the glucose used by the body at rest1. The function of non rapid eye movement sleep (NREMS), the largest portion of sleep by time, is uncertain. However, one salient feature of NREMS is a significant reduction in the rate of cerebral glucose utilization relative to wakefulness2-4. This and other findings have led to the widely held belief that sleep serves a function related to cerebral metabolism. Yet, the mechanisms underlying the reduction in cerebral glucose metabolism during NREMS remain to be elucidated.
	One phenomenon associated with NREMS that might impact cerebral metabolic rate is the occurrence of slow waves, oscillations at frequencies less than 4 Hz, in the electroencephalogram5,6. These slow waves detected at the level of the skull or cerebral cortical surface reflect the oscillations of underlying neurons between a depolarized/up state and a hyperpolarized/down state7. During the down state, cells do not undergo action potentials for intervals of up to several hundred milliseconds. Restoration of ionic concentration gradients subsequent to action potentials represents a significant metabolic load on the cell8; absence of action potentials during down states associated with NREMS may contribute to reduced metabolism relative to wake.
	Two technical challenges had to be addressed in order for this hypothetical relationship to be tested. First, it was necessary to measure cerebral glycolytic metabolism with a temporal resolution reflective of the dynamics of the cerebral EEG (that is, over seconds rather than minutes). To do so, we measured the concentration of lactate, the product of aerobic glycolysis, and therefore a readout of the rate of glucose metabolism in the brains of mice. Lactate was measured using a lactate oxidase based real time sensor embedded in the frontal cortex. The sensing mechanism consists of a platinum-iridium electrode surrounded by a layer of lactate oxidase molecules. Metabolism of lactate by lactate oxidase produces hydrogen peroxide, which produces a current in the platinum-iridium electrode. So a ramping up of cerebral glycolysis provides an increase in the concentration of substrate for lactate oxidase, which then is reflected in increased current at the sensing electrode. It was additionally necessary to measure these variables while manipulating the excitability of the cerebral cortex, in order to isolate this variable from other facets of NREMS.
	We devised an experimental system for simultaneous measurement of neuronal activity via the elecetroencephalogram, measurement of glycolytic flux via a lactate biosensor, and manipulation of cerebral cortical neuronal activity via optogenetic activation of pyramidal neurons. We have utilized this system to document the relationship between sleep-related electroencephalographic waveforms and the moment-to-moment dynamics of lactate concentration in the cerebral cortex. The protocol may be useful for any individual interested in studying, in freely behaving rodents, the relationship between neuronal activity measured at the electroencephalographic level and cellular energetics within the brain.

A procedure is described for manipulating the activity of cerebral cortical pyramidal neurons optogenetically while the electroencephalogram, electromyogram, and cerebral lactate concentration are monitored. Experimental recordings are performed on cable-tethered mice while they undergo spontaneous sleep/wake cycles. Optogenetic equipment is assembled in our laboratory; recording equipment is commercially available.

同时脑电图，实时测量的啮齿动物的大脑皮质中的神经元活动的乳酸浓度与Optogenetic的操作

Although the brain represents less than 5% of the body  by mass, it utilizes approximately one quarter of the glucose used by the body  at rest1. The ...

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

When rodents have free access to a running wheel in their home cage, voluntary use of this wheel will depend on the time of day1-5. Nocturnal rodents, including rats, hamsters, and mice, are active during the night and relatively inactive during the day. Many other behavioral and physiological measures also exhibit daily rhythms, but in rodents, running-wheel activity serves as a particularly reliable and convenient measure of the output of the master circadian clock, the suprachiasmatic nucleus (SCN) of the hypothalamus. In general, through a process called entrainment, the daily pattern of running-wheel activity will naturally align with the environmental light-dark cycle (LD cycle; e.g. 12 hr-light:12 hr-dark). However circadian rhythms are endogenously generated patterns in behavior that exhibit a ~24 hr period, and persist in constant darkness. Thus, in the absence of an LD cycle, the recording and analysis of running-wheel activity can be used to determine the subjective time-of-day. Because these rhythms are directed by the circadian clock the subjective time-of-day is referred to as the circadian time (CT). In contrast, when an LD cycle is present, the time-of-day that is determined by the environmental LD cycle is called the zeitgeber time (ZT).
Although circadian rhythms in running-wheel activity are typically linked to the SCN clock6-8, circadian oscillators in many other regions of the brain and body9-14 could also be involved in the regulation of daily activity rhythms. For instance, daily rhythms in food-anticipatory activity do not require the SCN15,16 and instead, are correlated with changes in the activity of extra-SCN oscillators17-20. Thus, running-wheel activity recordings can provide important behavioral information not only about the output of the master SCN clock, but also on the activity of extra-SCN oscillators. Below we describe the equipment and methods used to record, analyze and display circadian locomotor activity rhythms in laboratory rodents.

Circadian rhythms in voluntary wheel-running activity in mammals are tightly coupled to the molecular oscillations of a master clock in the brain. As such, these daily rhythms in behavior can be used to study the influence of genetic, pharmacological, and environmental factors on the functioning of this circadian clock.

运行轮活动在啮齿类动物的昼夜节律的记录和分析

When rodents have free access to a running wheel in their home cage, voluntary use of this wheel will depend on the time of day1-5. Nocturnal rodents, ...

Light Preference Assay to Study Innate and Circadian Regulated Photobehavior in Drosophila Larvae

Light acts as environmental signal to control animal behavior at various levels. The Drosophila larval nervous system is used as a unique model to answer basic questions on how light information is processed and shared between rapid and circadian behaviors. Drosophila larvae display a stereotypical avoidance behavior when exposed to light. To investigate light dependent behaviors comparably simple light-dark preference tests can be applied. In vertebrates and arthropods the neural pathways involved in sensing and processing visual inputs partially overlap with those processing photic circadian information. The fascinating question of how the light sensing system and the circadian system interact to keep behavioral outputs coordinated remains largely unexplored. Drosophila is an impacting biological model to approach these questions, due to a small number of neurons in the brain and the availability of genetic tools for neuronal manipulation. The presented light-dark preference assay allows the investigation of a range of visual behaviors including circadian control of phototaxis.

Light Preference Assay to Study Innate and Circadian Regulated Photobehavior in Drosophila Larvae

Here we describe a light-dark preference test for Drosophila larva. This assay provides information about innate and circadian regulation of light sensing and processing photobehavior.

光偏好的检测，以研究的先天和昼夜调节感光特性<em&gt;果蝇</em&gt;幼虫

Light acts as environmental signal to control animal behavior at various levels. The Drosophila larval nervous system is used as a unique model to answer ...

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such behavior is spontaneous locomotor activity. Here we describe our protocol that utilizes Drosophila population monitors and a tracking system that allows continuous monitoring of the spontaneous locomotor activity of flies for several days at a time. This method is simple, reliable, and objective and can be used to examine the effects of aging, sex, changes in caloric content of food, addition of drugs, or genetic manipulations that mimic human diseases.

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster are useful in studying genetic or environmental manipulations that affect behaviors such as spontaneous locomotor activity.&#160; Here we describe a protocol that utilizes monitors with infrared beams and data analysis software to quantify spontaneous locomotor activity.&#160;

在自发活动的测定<em&gt;果蝇</em

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such ...

High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

Advances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other neurological diseases at an increasing speed. However, little is known about the molecular mechanisms that underlie these disorders. The genetic, molecular, and behavioral toolbox of Drosophila melanogaster makes this model organism particularly useful to characterize new disease genes and mechanisms in a high-throughput manner. Nevertheless, high-throughput screens require efficient and reliable assays that, ideally, are cost-effective and allow for the automatized quantification of traits relevant to these disorders. The island assay is a cost-effective and easily set-up method to evaluate Drosophila locomotor behavior. In this assay, flies are thrown onto a platform from a fixed height. This induces an innate motor response that enables the flies to escape from the platform within seconds. At present, quantitative analyses of filmed island assays are done manually, which is a laborious undertaking, particularly when performing large screens.
This manuscript describes the &#34;Drosophila Island Assay&#34; and &#34;Island Assay Analysis&#34; algorithms for&#160;high-throughput, automated data processing and quantification of island assay data. In the setup, a simple webcam connected to a laptop collects an image series of the platform while the assay is performed. The &#34;Drosophila Island Assay&#34; algorithm developed for the open-source software Fiji processes these image series and quantifies, for each experimental condition, the number of flies on the platform over time. The &#34;Island Assay Analysis&#34; script, compatible with the free software R, was developed to automatically process the obtained data and to calculate whether treatments/genotypes are statistically different. This greatly improves the efficiency of the island assay and makes it a powerful readout for basic locomotion and flight behavior. It can thus be applied to large screens investigating fly locomotor ability, Drosophila models of movement disorders, and drug efficacy.

High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

The island assay is a relatively new, cost-effective assay that can be used to evaluate the basic locomotor behavior of Drosophila melanogaster. This manuscript describes algorithms for automatic data processing and objective quantification of island assay data, making this assay a sensitive, high-throughput readout for large genetic or pharmacological screens.

果蝇岛试验中运动行为的高通量分析

Advances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other ...

Single-cell Resolution Fluorescence Live Imaging of Drosophila Circadian Clocks in Larval Brain Culture

The circadian pacemaker circuit orchestrates rhythmic behavioral and physiological outputs coordinated with environmental cues, such as day/night cycles. The molecular clock within each pacemaker neuron generates circadian rhythms in gene expression, which underlie the rhythmic neuronal functions essential to the operation of the circuit. Investigation of the properties of the individual molecular oscillators in different subclasses of pacemaker neurons and their interaction with neuronal signaling yields a better understanding of the circadian pacemaker circuit. Here, we present a time-lapse fluorescent microscopy approach developed to monitor the molecular clockwork in clock neurons of cultured Drosophila larval brain. This method allows the multi-day recording of the rhythms of genetically encoded fluorescent circadian reporters at single-cell resolution. This setup can be combined with pharmacological manipulations to closely analyze real-time response of the molecular clock to various compounds. Beyond circadian rhythms, this multipurpose method in combination with powerful Drosophila genetic techniques offers the possibility to study diverse neuronal or molecular processes in live brain tissue.

Single-cell Resolution Fluorescence Live Imaging of Drosophila Circadian Clocks in Larval Brain Culture

The goal of this protocol is to establish ex vivo Drosophila larval brain culture optimized to monitor circadian molecular rhythms with long-term fluorescence time-lapse imaging. The application of this method to pharmacological assays is also discussed.

单细胞分辨荧光活成像在幼虫脑培养中的果蝇昼夜节律时钟

The circadian pacemaker circuit orchestrates rhythmic behavioral and physiological outputs coordinated with environmental cues, such as day/night cycles. ...