我们感谢韩俊海教授实验室成员的讨论和评论。这项工作得到了国家自然科学基金32170970 to Y.T和江苏省"花青蓝项目"的支持。

该协议使用来自布卢明顿果蝇库存中心的30天大w1118苍蝇（BDSC_3605，参见材料表）。
1.陈年果蝇的制备
<ol><li>食物准备<ol><li>通过混合 50 g/L 玉米片、110 g/L 糖、5 g/L 琼脂和 25 g/L 酵母来制备标准玉米淀粉培养基。用水加热玉米片和酵母糊化，然后将所有物质完全溶解。</li>
		<li>当培养基冷却至50-60°C时，加入6 mL/L丙酸，并迅速装入培养瓶中。</li>
	</ol></li>
	<li>苍蝇饲养和老年苍蝇的准备<ol><li>在装有标准玉米淀粉培养基的瓶子中培育苍蝇菌株 w1118，并将瓶子置于25°C，68%相对湿度，500-1000勒克斯照明条件和12小时:12小时光照:黑暗循环的恒温培养箱中。</li>
		<li>根据苍蝇的生长周期，每7天将苍蝇转移到一个新瓶子中，保持同一瓶子中个体的年龄一致。</li>
		<li>转移后 3 天收集从原瓶中孵化的新一批苍蝇，并将它们放入新瓶中。遵循每 7 天更换一次瓶子的原则，它们将被培养到 30 天左右。</li>
	</ol></li>
</ol>2、药用食品和玻璃管的制备
注:玻璃管制备的程序遵循Jin等人的工作，并进行了修改34。
<ol><li>玻璃管的清洁和干燥<ol><li>将玻璃管（直径5mm×长65mm，见 材料表）放入大烧杯中，浸泡，用双蒸水煮沸20分钟。重复 3 次。</li>
		<li>取出并捆扎玻璃管，用双蒸水冲洗3-5次，放入烤箱晾干。</li>
	</ol></li>
	<li>简单培养基（100 mL）的制备<ol><li>将 1.5 g 琼脂和 5 g 蔗糖溶解在双蒸水中，加热并浓缩至 100 mL。</li>
		<li>当培养基冷却至约70°C时加入600μL丙酸，防止其使用恒温水浴固化。</li>
		<li>将约4mL简单培养基和利血平（参见 材料表）加入10mL小烧杯中，直至药物达到20μM或50μM。 在阴性对照组中加入二甲基亚砜（DMSO）至0.2%的浓度。</li>
	</ol></li>
	<li>装药玻璃管的制备<ol><li>为了促进介质的流动，小心地将合适长度的玻璃管插入小烧杯中。由于大气压力，介质会自然进入玻璃管。</li>
		<li>当培养基完全凝固时，拉出玻璃管，擦拭外壁，得到一端装有药物培养基的监测玻璃管。</li>
		<li>将固体石蜡在烧杯中加热至在70°C熔化，将靠近食物的玻璃管末端放入石蜡液中约5mm，然后迅速取出。等待石蜡凝固以密封玻璃管的食物端。</li>
	</ol></li>
</ol>3. 实验设计与苍蝇处理
<ol><li>按照 表1设计苍蝇处理的实验。</li>
</ol>4. 果蝇 组装和睡眠监测
注: 果蝇 组装的程序遵循Jin等人34 的工作，并进行了修改。
<ol><li>用CO2 气体麻醉苍蝇，将其放入石蜡密封的玻璃管中（每管一个），并用吸水棉球堵住非食物端，以防止苍蝇逃逸，保证空气流通。</li>
	<li>将管子加载到红外监视器上进行监测。<ol><li>将装有苍蝇的玻璃管沿同一方向组装到红外监视器上，并记录每种药物对应的监视器编号和孔数。</li>
		<li>调整每个管子的对齐方式，使红外线垂直穿过苍蝇活动范围的中心。</li>
		<li>将显示器置于位于苍蝇睡眠暗室中的25°C培养箱内，遵循指定的设置:25°C温度，Zeitgeber 12（ZT12）（相当于当地时间08:00 p.m.）和ZT24（相当于当地时间08:00 a.m.）。这种设置确保苍蝇经历 12 小时的光明和黑暗交替时期。 注意: 在监测数据收集完成之前尽量不要打开门，以便在监测期间保持培养箱内环境稳定。</li>
		<li>使用 DAM2 系统开始监控（参见 材料表）。</li>
		<li>监控完成后，从系统下载收集的.txt格式数据。</li>
	</ol></li>
</ol>5. 数据处理
注意:使用 DAM 系统、DAMFileScan107 和 SCAMP 进行数据处理是根据其官方网站上的说明进行的 web网站（见 材料表）。
<ol><li>将上述txt文件导入DAMFileScan107软件进行扫描，根据需要进行分割，得到睡眠数据。<ol><li>在启动监视器后的第三天早上将分割数据的开始时间设置为8:01（1分钟分割）或8:00（30分钟分割），终止时间为开始时间后三天的上午8:00（图2A1）。 注意:苍蝇必须适应监测环境至少一天。因此，可以将拆分数据开始时间设置为监视器开始后第三天的上午 8 点。</li>
		<li>以 1 分钟和 30 分钟的间隔拆分数据。将选项"Bin Length"更改为 1 分钟，将选项"Output File Type"更改为 Channel files，重命名并输出。30分钟数据分割方法同上（图2A2-5）。 注意:以 1 min 和 30 min 的间隔进行数据分段时，两个文件的最终重命名应保持一致;否则，在后续的 Matlab 处理过程中可能无法读取。如有必要，可以在输出后更改文件名，以方便区分。</li>
	</ol></li>
	<li>使用SCAMP2020进行数据处理<ol><li>在Matlab中打开程序包SCAMP2020，然后双击Vecsey Sleep and Circadian Analysis MATLAB程序（SCAMP）（图2B）。</li>
		<li>将其子文件夹"Vecsey SCAMP Scripts"添加到路径中，在该文件夹中找到文件"scamp.m"，然后运行它。在以下弹出窗口中，依次选择进程 1 分钟和 30 分钟文件夹（图 2C、D）。</li>
		<li>选择一个监视器，单击 "加载单个查看 图"进行预览（图3A1），然后检查显示的图像。取消选中死苍蝇的相应通道（图3A2， 图3B）。</li>
		<li>重复上述步骤以检查所有显示器。</li>
		<li>根据要测试的相应药物重命名每个监视器中的每个通道（图3A3），选择所有监视器，然后单击"分析所选数据"进行分析（图3A4）。</li>
		<li>默认为所选选项，单击" 分析所选箱"，选中" 导出数据"，最后单击 "GRAPH 30 min Data Types for All Days for Selected Groups"和"EXPORT All Data "以输出结果（图3C）。</li>
	</ol></li>
	<li>从CSV文件中选择名为s30的文件，找到每个监视器对应的平均值和标准误差数据，备份到Excel进行修改和调整，粘贴到GraphPad Prism中（见材料表）绘制睡眠状态图（图4A，B）。</li>
	<li>找到名为"stdur"的文件，计算三天内每只苍蝇的白天、夜间和总睡眠的平均值（图4A，C）。将数据粘贴到Prism软件中，完成差异测试并绘制图表。</li>
</ol>

推进睡眠障碍治疗:一种基于果 蝇的筛查方法

<ol>
	<li>Le Bon, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relationships+between+REM+and+NREM+in+the+NREM-REM+sleep+cycle:+a+review+on+competing+concepts.">Relationships between REM and NREM in the NREM-REM sleep cycle: a review on competing concepts.</a> Sleep Medicine. 70, 6-16 (2020).</li><li>Krueger, J. M., Frank, M. G., Wisor, J. P., Roy, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+function:+Toward+elucidating+an+enigma.">Sleep function: Toward elucidating an enigma.</a> Sleep Medicine Reviews. 28, 46-54 (2016).</li><li>Ohayon, M. M., Carskadon, M. A., Guilleminault, C., Vitiello, M. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Meta-analysis+of+quantitative+sleep+parameters+from+childhood+to+old+age+in+healthy+individuals:+developing+normative+sleep+values+across+the+human+lifespan.">Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan.</a> Sleep. 27 (7), 1255-1273 (2004).</li><li>Li, S. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyperexcitable+arousal+circuits+drive+sleep+instability+during+aging.">Hyperexcitable arousal circuits drive sleep instability during aging.</a> Science. 375 (6583), eabh3021 (2022).</li><li>Rodriguez, J. C., Dzierzewski, J. M., Alessi, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+problems+in+the+elderly.">Sleep problems in the elderly.</a> Medical Clinics of North America. 99 (2), 431-439 (2015).</li><li>Gulia, K. K., Kumar, V. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+disorders+in+the+elderly:+a+growing+challenge.">Sleep disorders in the elderly: a growing challenge.</a> Psychogeriatrics. 18 (3), 155-165 (2018).</li><li>Wolkove, N., Elkholy, O., Baltzan, M., Palayew, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+and+aging:+1.+Sleep+disorders+commonly+found+in+older+people.">Sleep and aging: 1. Sleep disorders commonly found in older people.</a> Canadian Medical Association Journal. 176 (9), 1299-1304 (2007).</li><li>Suzuki, K., Miyamoto, M., Hirata, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+disorders+in+the+elderly:+Diagnosis+and+management.">Sleep disorders in the elderly: Diagnosis and management.</a> Journal of General and Family Medicine. 18 (2), 61-71 (2017).</li><li>Foley, D. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+complaints+among+elderly+persons+-+an+epidemiologic-study+of+3+communities.">Sleep complaints among elderly persons - an epidemiologic-study of 3 communities.</a> Sleep. 18 (6), 425-432 (1995).</li><li>Yu, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insomnia+Severity+Index:+psychometric+properties+with+Chinese+community-dwelling+older+people.">Insomnia Severity Index: psychometric properties with Chinese community-dwelling older people.</a> Journal of Advanced Nursing. 66 (10), 2350-2359 (2010).</li><li>Hoevenaar-Blom, M. P., Spijkerman, A. M., Kromhout, D., van den Berg, J. F., Verschuren, W. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+duration+and+sleep+quality+in+relation+to+12-year+cardiovascular+disease+incidence:+the+MORGEN+study.">Sleep duration and sleep quality in relation to 12-year cardiovascular disease incidence: the MORGEN study.</a> Sleep. 34 (11), 1487-1492 (2011).</li><li>Rebok, G. W., Rovner, B. W., Folstein, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep+disturbance+and+Alzheimer's+disease:+relationship+to+behavioral+problems.">Sleep disturbance and Alzheimer's disease: relationship to behavioral problems.</a> Aging (Milano). 3 (2), 193-196 (1991).</li><li>Schroeck, J. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+safety+and+efficacy+of+sleep+medicines+in+older+adults.">Review of safety and efficacy of sleep medicines in older adults.</a> Clinical Therapeutics. 38 (11), 2340-2372 (2016).</li><li>Pericic, D., Strac, D. S., Jembrek, M. J., Vlainic, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Allosteric+uncoupling+and+up-regulation+of+benzodiazepine+and+GABA+recognition+sites+following+chronic+diazepam+treatment+of+HEK+293+cells+stably+transfected+with+alpha1beta2gamma2S+subunits+of+GABA+(A)+receptors.">Allosteric uncoupling and up-regulation of benzodiazepine and GABA recognition sites following chronic diazepam treatment of HEK 293 cells stably transfected with alpha1beta2gamma2S subunits of GABA (A) receptors.</a> Naunyn-Schmiedeberg's Archives of Pharmacology. 375 (3), 177-187 (2007).</li><li>Lader, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=History+of+benzodiazepine+dependence.">History of benzodiazepine dependence.</a> Journal of Substance Abuse Treatment. 8 (1-2), 53-59 (1991).</li><li>Chen, P. L., Lee, W. J., Sun, W. Z., Oyang, Y. J., Fuh, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risk+of+dementia+in+patients+with+insomnia+and+long-term+use+of+hypnotics:+a+population-based+retrospective+cohort+study.">Risk of dementia in patients with insomnia and long-term use of hypnotics: a population-based retrospective cohort study.</a> Plos One. 7 (11), e49113 (2012).</li><li>Kang, D. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zolpidem+use+and+risk+of+fracture+in+elderly+insomnia+patients.">Zolpidem use and risk of fracture in elderly insomnia patients.</a> Journal of Preventive Medicine and Public Health. 45 (4), 219-226 (2012).</li><li>Kao, C. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relationship+of+zolpidem+and+cancer+risk:+a+Taiwanese+population-based+cohort+study.">Relationship of zolpidem and cancer risk: a Taiwanese population-based cohort study.</a> Mayo Clinic Protocols. 87 (5), 430-436 (2012).</li><li>Sateia, M. J., Kirby-Long, P., Taylor, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficacy+and+clinical+safety+of+ramelteon:+an+evidence-based+review.">Efficacy and clinical safety of ramelteon: an evidence-based review.</a> Sleep Medicine Reviews. 12 (4), 319-332 (2008).</li><li>Friedrich, M. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drug-induced+liver+injury+during+antidepressant+treatment:+results+of+amsp,+a+drug+surveillance+program.">Drug-induced liver injury during antidepressant treatment: results of amsp, a drug surveillance program.</a> The International Journal of Neuropsychopharmacology. 19 (4), pyv126 (2016).</li><li>Entzeroth, M., Flotow, H., Condron, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overview+of+high-throughput+screening.">Overview of high-throughput screening.</a> Current Protocols in Pharmacology. Chapter 9, (2009).</li><li>Ferreira, L. G., Dos Santos, R. N., Oliva, G., Andricopulo, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+docking+and+structure-based+drug+design+strategies.">Molecular docking and structure-based drug design strategies.</a> Molecules. 20 (7), 13384-13421 (2015).</li><li>Campbell, S. S., Tobler, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Animal+sleep+-+a+review+of+sleep+duration+across+phylogeny.">Animal sleep - a review of sleep duration across phylogeny.</a> Neuroscience and Biobehavioral Reviews. 8 (3), 269-300 (1984).</li><li>Hendricks, J. C., 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=The+need+for+a+simple+animal+model+to+understand+sleep.">The need for a simple animal model to understand sleep.</a> Progress in Neurobiology. 61 (4), 339-351 (2000).</li><li>Hendricks, J. C., et al. <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 (1), 129-138 (2000).</li><li>Shaw, P. J., Cirelli, C., Greenspan, R. J., Tononi, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correlates+of+sleep+and+waking+in+Drosophila+melanogaster.">Correlates of sleep and waking in Drosophila melanogaster.</a> Science. 287 (5459), 1834-1837 (2000).</li><li>Ly, S., Pack, A. I., Naidoo, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neurobiological+basis+of+sleep:+Insights+from+Drosophila.">The neurobiological basis of sleep: Insights from Drosophila.</a> Neuroscience &amp; Biobehavioral Reviews. 87, 67-86 (2018).</li><li>Jeibmann, A., Paulus, W. <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+as+a+model+organism+of+brain+diseases.">Drosophila melanogaster as a model organism of brain diseases.</a> International Journal of Molecular Sciences. 10 (2), 407-440 (2009).</li><li>Morse, D., Sassone-Corsi, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time+after+time:+inputs+to+and+outputs+from+the+mammalian+circadian+oscillators.">Time after time: inputs to and outputs from the mammalian circadian oscillators.</a> Trends in Neuroscience. 25 (12), 632-637 (2002).</li><li>De Nobrega, A. K., Lyons, L. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drosophila:+an+emergent+model+for+delineating+interactions+between+the+circadian+clock+and+drugs+of+abuse.">Drosophila: an emergent model for delineating interactions between the circadian clock and drugs of abuse.</a> Neural Plasticity. 2017, 4723836 (2017).</li><li>Reppert, S. M., Weaver, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordination+of+circadian+timing+in+mammals.">Coordination of circadian timing in mammals.</a> Nature. 418 (6901), 935-941 (2002).</li><li>Koudounas, S., Green, E. W., Clancy, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+and+variability+of+sleep+and+activity+as+biomarkers+of+ageing+in+Drosophila.">Reliability and variability of sleep and activity as biomarkers of ageing in Drosophila.</a> Biogerontology. 13 (5), 489-499 (2012).</li><li>Nall, A. H., 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=Small-molecule+screen+in+adult+Drosophila+identifies+VMAT+as+a+regulator+of+sleep.">Small-molecule screen in adult Drosophila identifies VMAT as a regulator of sleep.</a> Journal of Neuroscience. 33 (19), 8534-8464 (2013).</li><li>Jin, X., Gu, P., Han, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protocol+for+Drosophila+sleep+deprivation+using+single-chip+board.">Protocol for Drosophila sleep deprivation using single-chip board.</a> STAR Protocols. 2 (4), 100827 (2021).</li><li>Kashyap, A., Singh, P. K., Silakari, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Counting+on+fragment+based+drug+design+approach+for+drug+discovery.">Counting on fragment based drug design approach for drug discovery.</a> Current Topics in Medicinal Chemistry. 18 (27), 2284-2293 (2018).</li><li>Qi, W., Ding, D., Salvi, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cytotoxic+effects+of+dimethyl+sulphoxide+(DMSO)+on+cochlear+organotypic+cultures.">Cytotoxic effects of dimethyl sulphoxide (DMSO) on cochlear organotypic cultures.</a> Hearing Research. 236 (1-2), 52-60 (2008).</li><li>Nishimura, M., Ueda, N., Naito, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+dimethyl+sulfoxide+on+the+gene+induction+of+cytochrome+P450+isoforms,+UGT-dependent+glucuronosyl+transferase+isoforms,+and+ABCB1+in+primary+culture+of+human+hepatocytes.">Effects of dimethyl sulfoxide on the gene induction of cytochrome P450 isoforms, UGT-dependent glucuronosyl transferase isoforms, and ABCB1 in primary culture of human hepatocytes.</a> Biological and Pharmaceutical Bulletin. 26 (7), 1052-1056 (2003).</li><li>Solovev, I. A., Shaposhnikov, M. V., Moskalev, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chronobiotics+KL001+and+KS15+extend+lifespan+and+modify+circadian+rhythms+of+Drosophila+melanogaster.">Chronobiotics KL001 and KS15 extend lifespan and modify circadian rhythms of Drosophila melanogaster.</a> Clocks Sleep. 3 (3), 429-441 (2021).</li><li>Cavas, M., Beltran, D., Navarro, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Behavioural+effects+of+dimethyl+sulfoxide+(DMSO):+changes+in+sleep+architecture+in+rats.">Behavioural effects of dimethyl sulfoxide (DMSO): changes in sleep architecture in rats.</a> Toxicology Letters. 157 (3), 221-232 (2005).</li><li>Pfeiffenberger, C., Lear, B. C., Keegan, K. P., Allada, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Locomotor+activity+level+monitoring+using+the+Drosophila+Activity+Monitoring+(DAM)+System.">Locomotor activity level monitoring using the Drosophila Activity Monitoring (DAM) System.</a> Cold Spring Harbor Protocols. 2010 (11), 5518 (2010).</li><li>Gilestro, G. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Video+tracking+and+analysis+of+sleep+in+Drosophila+melanogaster.">Video tracking and analysis of sleep in Drosophila melanogaster.</a> Nature Protocols. 7 (5), 995-1007 (2012).</li><li>Branson, K., Robie, A. A., Bender, J., Perona, P., Dickinson, M. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+ethomics+in+large+groups+of+Drosophila.">High-throughput ethomics in large groups of Drosophila.</a> Nature Methods. 6 (6), 451-457 (2009).</li><li>Kabra, M., Robie, A. A., Rivera-Alba, M., Branson, S., Branson, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=JAABA:+interactive+machine+learning+for+automatic+annotation+of+animal+behavior.">JAABA: interactive machine learning for automatic annotation of animal behavior.</a> Nature Methods. 10 (1), 64-67 (2013).</li><li>Donelson, N. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+positional+tracking+for+long-term+analysis+of+Drosophila+sleep+and+locomotion+using+the+&amp;#34;tracker&amp;#34;+program.">High-resolution positional tracking for long-term analysis of Drosophila sleep and locomotion using the &amp;#34;tracker&amp;#34; program.</a> Plos One. 7 (5), e37250 (2012).</li><li>Cichewicz, K., Hirsh, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ShinyR-DAM:+a+program+analyzing+Drosophila+activity,+sleep+and+circadian+rhythms.">ShinyR-DAM: a program analyzing Drosophila activity, sleep and circadian rhythms.</a> Communications Biology. 1, 25 (2018).</li></ol>

作者声明没有利益冲突。

所述方法适用于中小型安眠药物的快速筛选。目前，大多数主流的高通量药物筛选方法都是基于生化和细胞水平。例如，检查受体的结构和性质以寻找可以与其结合的特定配体22。另一种方法是使用核磁共振 （NMR） 和质谱法35 分析所选药物分子片段的结合模式和强度。然而，这些方法往往具有相对较高的筛选错误率，通过它们选择的药物在动物或临床实验中往往没有显示出效果。药物在体内的疗效受药物吸收、分布、代谢、排泄等多种因素影响，导致误筛率高。相比之下，尽管与高通量方法相比，我们提出的方法具有较小的筛选规模，但它通过直接观察药物对表型的影响，提供了一种更直接和更具成本效益的方法。这证明了使用 果蝇 模型进行有效药物筛选和药物靶点鉴定的潜力。
果蝇 具有保守的睡眠调节机制，并表现出与衰老相关的睡眠障碍。我们观察到30日龄雌性果蝇的睡眠持续时间明显短于7日龄果蝇，而30日龄雄性果蝇的睡眠持续时间与7日龄果蝇的睡眠持续时间没有显著差异（图6）。因此，选择了30日龄的雌性果蝇进行目前的实验。进行了多轮筛选过程，以尽量减少意外因素干扰。第一轮药物浓度设定为20μM，以避免可能导致苍蝇死亡的毒副作用。在第二轮筛选中，将药物浓度增加到50μM，以评估药物在不同浓度下的效果。从第二轮中选择的药物以 20 μM 和 50 μM 的剂量给予雄性果蝇，以评估药物作用的性别差异。这使得人们可以筛选出始终如一地表现出睡眠相关作用的药物。例如，利血平先前已被证明可以增加 4-6 天31 岁的成年苍蝇的睡眠。我们成功地在使用老年苍蝇的模型中复制了这一结果，其中老年雌性在服用利血平后睡眠显着增加（图5）。
DMSO用于溶解药物，但应考虑其潜在毒性。先前的研究表明，培养基中浓度为0.1%至0.25%的DMSO在24小时内不会伤害大鼠毛细胞，而浓度为0.5%至6%的DMSO可显着增加细胞死亡36。同样，已经发现0.1%或更低的DMSO浓度不影响人肝细胞中关键药物代谢相关酶或转运蛋白的表达。尽管如此，较高的浓度仍可诱导表达37的变化。然而，应该注意的是，已发现 0.1% DMSO 显着影响雌性果蝇的寿命，但不会影响雄性果蝇的寿命 38.此外，腹膜内施用 15% 和 20% DMSO 已被证明会干扰大鼠的睡眠39。为了减轻DMSO的潜在毒性，我们将其浓度保持在0.2%以下。
目前，有两种主要方法用于表征 果蝇的行为。一种方法是基于视频分析，它提供了丰富的行为参数，包括飞行位置、速度和身体部位的细微运动。另一种方法基于红外光束断裂，例如DAM系统。40. 然而，需要注意的是，某些视频分析工具（如 PySolo）是为研究多只单一居民苍蝇而设计的，限制了可以放置在相机下的苍蝇数量41。C-trax42 和 JAABA43 等其他工具可以执行种群跟踪，但计算成本高昂且耗时。对于高通量筛查，捕获苍蝇的整体睡眠持续时间通常就足够了，不需要精确的运动参数。因此，基于红外束断裂的广泛应用和高度扩展的方法是首选。但是，这种方法也有其局限性。例如，如果苍蝇只在管子的一端移动而不中断红外光束，系统可能会错误地将其记录为睡眠，从而导致对睡眠的高估44。此外，在将苍蝇菌株用于筛选之前，仔细测试苍蝇菌株的运动性也很重要，以避免意外影响。
以下是一些成功设置的有用提示: （1） 为防止食物凝固后从小烧杯中取出时粘在玻璃管上，可以尝试在食物凝固之前将玻璃管垂直插入小烧杯底部。轻轻地来回拉动玻璃管，轻敲烧杯底部让空气进入，慢慢旋转烧杯将所有食物和玻璃管取出，然后小心地擦去玻璃管外壁上残留的食物可以有效。（2）用石蜡膜密封玻璃管食品端时，建议用水浴慢慢加热薄膜，直到石蜡融化。这种方法有助于避免药用食品在高温下剧烈飞溅和污染石蜡膜的问题。或者，可以使用小塑料盖进行密封，但要确保在密封过程中空气可能会进入，从而导致食物整体向上推。（3）值得考虑的是，一些强效的促进睡眠的药物最初可能导致对被测果蝇的错误判断为死亡。为了克服这个问题，建议设置浓度梯度，以便探索最佳药物浓度并重复实验。（4）考虑到药物的气味可能会影响苍蝇消耗的食物量和药物的摄入量，从而可能影响实验结果的准确性。因此，适当延长实验时间，保证苍蝇有充足的时间消耗尽可能多的药物，增强药物的蓄积效果是有益的。（5） 在数据处理方面，虽然许多大学和研究所都可以访问 Matlab 供公众使用，但对于尚未购买该程序的个人或研究机构来说，也有成本更低的替代方案。一个推荐的选项是 ShinyR-DAM v3.1 «Refresh»45。
总之，我们开发了一种分步程序来筛选治疗睡眠障碍的药物。使用表现出较短睡眠持续时间表型的较老苍蝇模型，验证了利血平在增加老年雌性果蝇睡眠时间方面的功效。该方法提供了一种具有巨大应用潜力的药物筛选新方法，为进一步的药物研究奠定了基础。虽然药物作用是根据表型评估的，但药物作用的潜在机制仍然未知。将进行进一步的研究，以调查睡眠障碍的病理学和睡眠的分子调节，从而阐明所涉及的药理机制。尽管 果蝇 的昼夜节律机制与人类振荡器有相似之处，但人类和果蝇之间睡眠控制机制的差异不容忽视。该协议为睡眠障碍的药物筛选提供了基本框架。然而，未来的研究将确定是否有任何筛选的药物可用于临床治疗，并阐明其作用机制。

睡眠是人类生存所必需的基本行为之一，其特征有两种主要状态:快速眼动（REM）睡眠和非快速眼动（NREM）睡眠1。NREM睡眠包括三个阶段:N1（清醒和睡眠之间的过渡）、N2（浅睡眠）和N3（深度睡眠、慢波睡眠），代表从清醒到深度睡眠的进展1。睡眠对身心健康起着至关重要的作用2.然而，衰老会降低成人的总睡眠时间、睡眠效率、慢波睡眠百分比和快速眼动睡眠百分比3.与慢波睡眠相比，老年人倾向于花更多的时间在浅睡眠中，使他们对夜间觉醒更敏感。随着觉醒次数的增加，平均睡眠时间减少，导致老年人睡眠模式碎片化，这可能与小鼠 Hcrt 神经元的过度兴奋有关4.此外，与年龄相关的昼夜节律机制下降有助于睡眠持续时间的早期转变 5,6。结合身体疾病、心理压力、环境因素和药物使用，这些因素使老年人更容易患上睡眠障碍，如失眠、快速眼动睡眠行为障碍、发作性睡病、周期性腿部运动、不宁腿综合征和睡眠呼吸障碍 7,8。
流行病学研究表明，睡眠障碍与老年人的慢性疾病密切相关9，包括抑郁症10，心血管疾病11和痴呆12。解决睡眠障碍在改善和治疗慢性病以及提高老年人的生活质量方面发挥着至关重要的作用。目前，患者主要依靠苯二氮卓类药物、非苯二氮卓类药物和褪黑激素受体激动剂等药物来改善睡眠质量13.然而，苯二氮卓类药物在长期使用后可导致受体下调和依赖性，在停药后引起严重的戒断症状14,15。非苯二氮卓类药物也有风险，包括痴呆16、骨折17 和癌症18。常用的褪黑激素受体激动剂雷美替胺可减少睡眠潜伏期，但不会增加睡眠持续时间，并且由于广泛的首过消除而存在肝功能相关问题19.阿戈美拉汀是一种褪黑激素受体激动剂和血清素受体拮抗剂，可改善与抑郁症相关的失眠，但也存在肝损伤的风险20。因此，迫切需要更安全的药物来治疗或缓解睡眠障碍。然而，目前基于分子和细胞实验的药物筛选策略，结合自动化系统和计算机分析，既昂贵又耗时21。基于结构的药物设计策略，依赖于受体结构和性质，需要对受体三维结构有清晰的认识，缺乏对药物作用的预测能力22。
2000 年，根据 Campbell 和 Tobler 在 1984 23 年提出的睡眠标准，研究人员建立了简单的动物模型来研究睡眠 24，包括果蝇黑腹果蝇，它表现出类似睡眠的状态25,26。尽管果蝇和人类在解剖学上存在差异，但许多调节果蝇睡眠的神经化学成分和信号通路在哺乳动物睡眠中是保守的，从而促进了人类神经系统疾病的研究27,28。果蝇也广泛用于昼夜节律研究，尽管果蝇和哺乳动物之间的核心振荡器存在差异29,30,31。因此，果蝇是研究睡眠行为和进行睡眠相关药物筛选的有价值的模式生物。
本研究提出了一种具有成本效益且简单的基于表型的方法，用于筛选使用老年苍蝇治疗睡眠障碍的小分子药物。 果蝇 的睡眠调节是高度保守的25，随着年龄的增长观察到的睡眠下降可能通过给药是可逆的。因此，这种基于睡眠表型的筛选方法可以直观地反映药物疗效。我们用正在研究的药物和食物的混合物喂养果蝇，使用 果蝇 活动监测器（DAM）32监测和记录睡眠行为，并使用MATLAB中的开源SCAMP2020数据包分析采集的数据（图1）。使用统计和绘图软件进行统计分析（见 材料表）。例如，我们通过展示利血平的实验数据来证明该协议的有效性，利血平是一种据报道可增加睡眠的囊泡单胺转运蛋白的小分子抑制剂33。该协议提供了一种有价值的方法来识别用于治疗与年龄相关的睡眠问题的药物。

<table><tbody><tr><td>Ager</td><td>BIOFROXX</td><td>8211KG001</td><td></td></tr><tr><td>Artificial Climate Box</td><td>PRANDT</td><td>PRX-1000A</td><td>official website:https://www.nbplt17.com/PLTXBS-Products-20643427/</td></tr><tr><td>DAM2 Drosophila Activity Monitor</td><td>TriKineics</td><td>DAM2</td><td>official website:https://www.trikinetics.com/</td></tr><tr><td>DAM2system</td><td>TriKineics</td><td>version:v3.03</td><td>official website:https://www.trikinetics.com/</td></tr><tr><td>DAMFileScan</td><td>TriKineics</td><td>version:1.0.7.0</td><td>official website:https://www.trikinetics.com/</td></tr><tr><td>Dimethyl Sulfoxide</td><td>SIGMA</td><td>276855</td><td></td></tr><tr><td>Drosophila Activity Monitoring Incubator</td><td>Tritech Research</td><td>DT2-CIRC-TK</td><td>official website:https://www.tritechresearch.com/DT2-CIRC-TK.html</td></tr><tr><td>Drosophila Bottles</td><td>Biologix</td><td>51-17720</td><td>official website:http://biologixgroup.com/goods.php?id=48</td></tr><tr><td>Drosophila: w&lt;sup&gt;1118&lt;/sup&gt;</td><td>Bloomington Drosophila Stock Center&amp;nbsp;</td><td>BDSC_3605</td><td></td></tr><tr><td>Excel</td><td>Microsoft</td><td>version:Excel 2016</td><td>official website:https://www.microsoftstore.com.cn/software/office/excel</td></tr><tr><td>Glass tubes</td><td>TriKinetics</td><td>PPT5x65</td><td>official website:https://www.trikinetics.com/</td></tr><tr><td>MATLABR2022b</td><td>MathWorks</td><td>version:9.13.0.2049777</td><td>official website:https://ww2.mathworks.cn/products/matlab.html</td></tr><tr><td>Prism</td><td>GraphPad</td><td>Version:Prism 8.0.1</td><td>official website:https://www.graphpad.com/features</td></tr><tr><td>Reserpine</td><td>MACKLIN</td><td>R817202-1g</td><td></td></tr><tr><td>Saccharose</td><td>SIGMA</td><td>1245GR500</td><td></td></tr><tr><td>SCAMP</td><td>Vecsey Lab</td><td>N/A</td><td>official website:https://academics.skidmore.edu/blogs/cvecsey/</td></tr></tbody></table>

high-throughput small molecule drug screening for age-related sleep disorders using drosophila melanogaster

睡眠是健康和整体幸福的重要组成部分，经常给老年人带来挑战，他们经常经历睡眠障碍，其特征是睡眠持续时间缩短和模式碎片化。这些睡眠中断也与老年人患各种疾病的风险增加有关，包括糖尿病、心血管疾病和心理障碍。不幸的是，现有的睡眠障碍药物与严重的副作用有关，例如认知障碍和成瘾。因此，迫切需要开发新的、更安全、更有效的睡眠障碍药物。然而，目前药物筛选方法的高成本和漫长的实验时间仍然是限制因素。
该协议描述了一种具有成本效益和高通量的筛选方法，该方法利用 黑腹果蝇，与哺乳动物相比，果蝇具有高度保守的睡眠调节机制，使其成为研究老年人睡眠障碍的理想模型。通过给老年苍蝇施用各种小化合物，我们可以评估它们对睡眠障碍的影响。这些苍蝇的睡眠行为使用红外监测设备记录，并使用开源数据包睡眠和昼夜节律分析MATLAB程序2020（SCAMP2020）进行分析。该协议为睡眠调节提供了一种低成本、可重复且高效的筛查方法。果蝇由于其生命周期短、饲养成本低、易于处理，是该方法的绝佳对象。举例来说，其中一种测试药物利血平证明了促进老年苍蝇睡眠时间的能力，突出了该协议的有效性。

利血平是囊泡单胺转运蛋白 （VMAT） 的小分子抑制剂，可抑制单胺重新摄取到突触前囊泡中，导致睡眠增加33。在 30 日龄的果蝇中检查了利血平的睡眠促进作用，对照组仅喂食溶剂二甲基亚砜 （DMSO）。在利血平组中，与DMSO组相比，老年果蝇在白天和晚上的睡眠都显着增加。图5A，E显示了连续三天利血平和DMSO苍蝇的睡眠模式，而图5B-D和图5F-H显示了睡眠数据的差异测试结果。为了消除药物只作用于一种性别的可能性，使用雄性果蝇重复实验。施用不同浓度的利血平，20μM和50μM，表明利血平浓度与促进睡眠呈正相关。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65787/65787fig01.jpg"> 图1:针对年龄相关睡眠障碍的小分子药物筛选实验过程。 老年苍蝇被放入一个小玻璃管中，里面装有含有待测试药物的食物。使用DAM系统连续监测睡眠模式三天。将采集的数据导入计算机进行处理、可视化和分析，从而得出结论。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig01large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65787/65787fig02.jpg"> 图 2:数据的扫描和划分。 （A） 数据选择和扫描，然后进行顺序时间分割。（B） "Vecsey Sleep and Circadian Analysis MATLAB Program （SCAMP）"文件夹的位置。（C） 将子文件夹"Vecsey SCAMP Scripts"添加到路径中。（D） 文件"scamp.m"的位置。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig02large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65787/65787fig03.jpg"> 图 3:睡眠数据的选择和处理。 （A） 预览苍蝇睡眠条件，取消选中死苍蝇通道，并对所选数据进行分组和分析。（B）果蝇睡眠预览，其中均匀的蓝色矩形表示活跃的睡眠，而均匀的蓝色矩形的某个时刻表明苍蝇已经死亡。死苍蝇用红色矩形标记。（C） 选定数据的分析和输出。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig03large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65787/65787fig04.jpg"> 图 4:睡眠数据分析结果 。 （A） 从 CSV 文件中选择 s30 和 stdur 文件。（B）"s30.csv"中每组睡眠平均值（SEM）的平均值和标准误差。（C） "stdur.csv"中每只苍蝇三天内白天（Bin1、Bin3、Bin5）、夜间（Bin2、Bin4、Bin6）和总睡眠时间的值。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig04large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65787/65787fig05.jpg"> 图5:用利血平治疗的老年苍蝇的睡眠状况。 （A） 喂食 0.2% DMSO、20 μM 利血平和 50 μM 利血平的老年女性 3 天内睡眠时间的示意图。（B-D）定量分析3天内有或没有药物的平均白天、夜间和总睡眠时间。结果表明，喂食利血平的老年女性的睡眠时间显着增加。N = 8 每组，单因素方差分析，**p < 0.01，***p < 0.001。（E） 喂食 0.2% DMSO、20 μM 利血平和 50 μM 利血平的老年男性 3 天内睡眠时间的示意图。（F-H）定量分析3天内有或没有药物的平均白天、夜间和总睡眠时间。结果表明，喂食利血平的男性睡眠时间增加。n = 16 每组，单因素方差分析，*p < 0.05，**p < 0.01。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig05large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65787/65787fig06.jpg"> 图6:幼蝇和老年苍蝇睡眠时间的比较。 （A） 年轻和老年雄性 3 天睡眠持续时间监测示意图。（B-D）对年轻和老年男性3天内平均白天、夜间和总睡眠时间的定量分析显示，差异无统计学意义。每组 n = 32，非配对 t 检验，n.s.，不显著。（E） 年轻和老年女性 3 天以上睡眠持续时间的示意图监测。（F-H）对年轻和老年女性 3 天内平均白天、夜间和总睡眠时间的定量分析表明，与年轻女性相比，老年女性的白天、夜间和总睡眠时间显着减少。每组 n = 32，非配对 t 检验，****p < 0.0001。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65787/65787fig06large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td>群</td>
			<td colspan="2">研究组</td>
			<td colspan="3">治疗</td>
			<td colspan="2">苍蝇的年龄和性别</td>
			<td colspan="2">苍蝇数量</td>
		</tr><tr><td><img alt="Equation 1" src="/files/ftp_upload/65787/65787eq01.jpg" style="margin: auto;"></td>
			<td colspan="2">普通控件</td>
			<td colspan="3">含 0.2% DMSO 的 4 mL 简单培养基 4 天</td>
			<td colspan="2">30 天 男性/女性</td>
			<td colspan="2">每组16只苍蝇</td>
		</tr><tr><td><img alt="Equation 2" src="/files/ftp_upload/65787/65787eq02.jpg" style="margin: auto;"></td>
			<td colspan="2">低剂量药物试验<img alt="Equation 6" src="/files/ftp_upload/65787/65787eq06.jpg" style="margin: auto;"></td>
			<td colspan="3">4 mL 含 20 μM 利血平的简单培养基 4 天</td>
			<td colspan="2">30天女性</td>
			<td colspan="2">每组16只苍蝇</td>
		</tr><tr><td><img alt="Equation 3" src="/files/ftp_upload/65787/65787eq03.jpg" style="margin: auto;"></td>
			<td colspan="2">大剂量药物试验<img alt="Equation 6" src="/files/ftp_upload/65787/65787eq06.jpg" style="margin: auto;"></td>
			<td colspan="3">4 mL 含 50 μM 利血平的简单培养基 4 天</td>
			<td colspan="2">30天女性</td>
			<td colspan="2">每组16只苍蝇</td>
		</tr><tr><td><img alt="Equation 4" src="/files/ftp_upload/65787/65787eq04.jpg" style="margin: auto;"></td>
			<td colspan="2">低剂量药物试验<img alt="Equation 7" src="/files/ftp_upload/65787/65787eq07v2.jpg" style="margin: auto;"></td>
			<td colspan="3">4 mL 含 20 μM 利血平的简单培养基 4 天</td>
			<td colspan="2">30天 男性</td>
			<td colspan="2">每组16只苍蝇</td>
		</tr><tr><td><img alt="Equation 5" src="/files/ftp_upload/65787/65787eq05.jpg" style="margin: auto;"></td>
			<td colspan="2">大剂量药物试验<img alt="Equation 7" src="/files/ftp_upload/65787/65787eq07v2.jpg" style="margin: auto;"></td>
			<td colspan="3">4 mL 含 50 μM 利血平的简单培养基 4 天</td>
			<td colspan="2">30天 男性</td>
			<td colspan="2">每组16只苍蝇</td>
		</tr></tbody></table>表1:苍蝇处理的实验设计。

Watch this Scientific Journal Video about Overcoming Challenges in Drosophila Sleep Measurement Using DAM System at JoVE.com

作者聚焦:使用 DAM 系统克服果蝇睡眠测量的挑战 

提出了一种高通量药物筛选方案，通过监测老年果蝇模型中 果蝇 的睡眠行为来改善睡眠。

使用黑腹果蝇对年龄相关睡眠障碍进行高通量小分子药物筛选

Sleep, an essential component of health and overall well-being, often presents challenges for older individuals who frequently experience sleep disorders ...

药物筛选技术包括高通量筛选，使用自动化进行药物发现，基于结构的设计，并根据结构找到受体结合分子，以及基于片段的设计，使用核磁共振和质谱来优化分子片段并鉴定化合物。DAM 系统通过检测红外光束砖来测量苍蝇睡眠。然而，如果苍蝇在管子的一端保持静止，或者苍蝇的移动性不高，这种方法可能会高估睡眠。此外，任何测试药物的顺序都可能影响蝇果的摄入量，从而可能扭曲实验结果。因此，我们的实验将结合各种拉伸来减轻这些因素并提高准确性。与基于视频分析的方法相比，我们的方法提供了高通量能力，降低了成本，并简化了操作。因此，实验数据的过程也相对简单，其中生成的图表直观地代表了药物的作用。

high-throughput-small-molecule-drug-screening-for-age-related-sleep

Nanyang Technological University

Research

Education

JoVE Journal

JoVE Core

Pharmacology

Behavior

High-Throughput Small Molecule Drug Screening For Age-Related Sleep Disorders Using Drosophila melanogaster

Unit 1

Pharmacotherapy of Depression and Anxiety Disorders

SCIENTISTS IN ACTION

2.2K 次观看.  Southeast University. 药物筛选技术包括高通量筛选，使用自动化进行药物发现，基于结构的设计，并根据结构找到受体结合分子，以及基于片段的设计，使用核磁共振和质谱来优化分子片段并鉴定化合物。DAM 系统通过检测红外光束砖来测量苍蝇睡眠。然而，如果苍蝇在管子的一端保持静止，或者苍蝇的移动性不高，这种方法可能会高估睡眠。此外，任何测试药物的顺序都可能影响蝇果的摄...

视频: 作者聚焦:使用 DAM 系统克服果蝇睡眠测量的挑战 

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

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) pacemakers or clocks. Malfunctions in the human circadian system are associated with numerous diseases or disorders. Much progress towards our understanding of the mechanisms underlying circadian rhythms has emerged from genetic screens whereby an easily measured behavioral rhythm is used as a read-out of clock function. Studies using Drosophila have made seminal contributions to our understanding of the cellular and biochemical bases underlying circadian rhythms. The standard circadian behavioral read-out measured in Drosophila is locomotor activity. In general, the monitoring system involves specially designed devices that can measure the locomotor movement of Drosophila. These devices are housed in environmentally controlled incubators located in a darkroom and are based on using the interruption of a beam of infrared light to record the locomotor activity of individual flies contained inside small tubes. When measured over many days, Drosophila exhibit daily cycles of activity and inactivity, a behavioral rhythm that is governed by the animal's endogenous circadian system. The overall procedure has been simplified with the advent of commercially available locomotor activity monitoring devices and the development of software programs for data analysis. We use the system from Trikinetics Inc., which is the procedure described here and is currently the most popular system used worldwide. More recently, the same monitoring devices have been used to study sleep behavior in Drosophila. Because the daily wake-sleep cycles of many flies can be measured simultaneously and only 1 to 2 weeks worth of continuous locomotor activity data is usually sufficient, this system is ideal for large-scale screens to identify Drosophila manifesting altered circadian or sleep properties.

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

We describe procedures for recording daily locomotor activity rhythms of Drosophila and subsequent data analysis. Locomotor activity rhythms are a reliable behavioral output of animal circadian clocks and are used as the standard readout of clock function when studying circadian mutants or examining how the environment regulates the circadian system.

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) ...

科研

神经科学

In Vivo Forward Genetic Screen to Identify Novel Neuroprotective Genes in Drosophila melanogaster

There is much to understand about the onset and progression of neurodegenerative diseases, including the underlying genes responsible. Forward genetic screening using chemical mutagens is a useful strategy for mapping mutant phenotypes to genes among Drosophila and other model organisms that share conserved cellular pathways with humans. If the mutated gene of interest is not lethal in early developmental stages of flies, a climbing assay can be conducted to screen for phenotypic indicators of decreased brain functioning, such as low climbing rates. Subsequently, secondary histological analysis of brain tissue can be performed in order to verify the neuroprotective function of the gene by scoring neurodegeneration phenotypes. Gene mapping strategies include meiotic and deficiency mapping that rely on these same assays can be followed by DNA sequencing to identify possible nucleotide changes in the gene of interest.

In Vivo Forward Genetic Screen to Identify Novel Neuroprotective Genes in Drosophila melanogaster

We present a protocol using a forward genetic approach to screen for mutants exhibiting neurodegeneration in Drosophila melanogaster. It incorporates a climbing assay, histology analysis, gene mapping and DNA sequencing to ultimately identify novel genes related to the process of neuroprotection.

在Vivo前向遗传屏幕识别新的神经保护基因在果蝇黑色素

There is much to understand about the onset and progression of neurodegenerative diseases, including the underlying genes responsible. Forward genetic ...

遗传学

Paired Nanoinjection and Electrophysiology Assay to Screen for Bioactivity of Compounds using the Drosophila melanogaster Giant Fiber System

Screening compounds for in vivo activity can be used as a first step to identify candidates that may be developed into pharmacological agents1,2. We developed a novel nanoinjection/electrophysiology assay that allows the detection of bioactive modulatory effects of compounds on the function of a neuronal circuit that mediates the escape response in Drosophila melanogaster3,4. Our in vivo assay, which uses the Drosophila Giant Fiber System (GFS, Figure 1) allows screening of different types of compounds, such as small molecules or peptides, and requires only minimal quantities to elicit an effect. In addition, the Drosophila GFS offers a large variety of potential molecular targets on neurons or muscles. The Giant Fibers (GFs) synapse electrically (Gap Junctions) as well as chemically (cholinergic) onto a Peripheral Synapsing Interneuron (PSI) and the Tergo Trochanteral Muscle neuron (TTMn)5. The PSI to DLMn (Dorsal Longitudinal Muscle neuron) connection is dependent on D&alpha;7 nicotinic acetylcholine receptors (nAChRs)6. Finally, the neuromuscular junctions (NMJ) of the TTMn and the DLMn with the jump (TTM) and flight muscles (DLM) are glutamatergic7-12. Here, we demonstrate how to inject nanoliter quantities of a compound, while obtaining electrophysiological intracellular recordings from the Giant Fiber System13 and how to monitor the effects of the compound on the function of this circuit. We show specificity of the assay with methyllycaconitine citrate (MLA), a nAChR antagonist, which disrupts the PSI to DLMn connection but not the GF to TTMn connection or the function of the NMJ at the jump or flight muscles.
Before beginning this video it is critical that you carefully watch and become familiar with the JoVE video titled "Electrophysiological Recordings from the Giant Fiber Pathway of D. melanogaster " from Augustin et al7, as the video presented here is intended as an expansion to this existing technique. Here we use the electrophysiological recordings method and focus in detail only on the addition of the paired nanoinjections and monitoring technique.

Paired Nanoinjection and Electrophysiology Assay to Screen for Bioactivity of Compounds using the Drosophila melanogaster Giant Fiber System

A rapid in vivo assay to test for neuromodulatory compounds using the Giant Fiber System (GFS) of Drosophila melanogaster is described. Nanoinjections in the head of the animal along with electrophysiological recordings of the GFS can reveal bioactivity of compounds on neurons or muscles.

电检测屏幕的配对Nanoinjection和生物活性化合物的使用果蝇巨人纤维系统

Screening compounds for in vivo activity can be used as a first step to identify candidates that may be developed into pharmacological agents1,2. We ...

Quantitative Measurement of the Immune Response and Sleep in Drosophila

A complex interaction between the immune response and host behavior has been described in a wide range of species. Excess sleep, in particular, is known to occur as a response to infection in mammals 1 and has also recently been described in Drosophila melanogaster2. It is generally accepted that sleep is beneficial to the host during an infection and that it is important for the maintenance of a robust immune system3,4. However, experimental evidence that supports this hypothesis is limited4, and the function of excess sleep during an immune response remains unclear. We have used a multidisciplinary approach to address this complex problem, and have conducted studies in the simple genetic model system, the fruitfly Drosophila melanogaster. We use a standard assay for measuring locomotor behavior and sleep in flies, and demonstrate how this assay is used to measure behavior in flies infected with a pathogenic strain of bacteria. This assay is also useful for monitoring the duration of survival in individual flies during an infection. Additional measures of immune function include the ability of flies to clear an infection and the activation of NF&kappa;B, a key transcription factor that is central to the innate immune response in Drosophila. Both survival outcome and bacterial clearance during infection together are indicators of resistance and tolerance to infection. Resistance refers to the ability of flies to clear an infection, while tolerance is defined as the ability of the host to limit damage from an infection and thereby survive despite high levels of pathogen within the system5. Real-time monitoring of NF&kappa;B activity during infection provides insight into a molecular mechanism of survival during infection. The use of Drosophila in these straightforward assays facilitates the genetic and molecular analyses of sleep and the immune response and how these two complex systems are reciprocally influenced.

Quantitative Measurement of the Immune Response and Sleep in Drosophila

To understand a link between the immune response and behavior, we describe a method to measure locomotor behavior in Drosophila during bacterial infection as well as the ability of flies to mount an immune response by monitoring survival, bacterial load, and real-time activity of a key regulator of innate immunity, NF&kappa;B.

定量测定的免疫反应和睡眠模式<em&gt;果蝇</em

A complex interaction between the immune response and  host behavior has been described in a wide range of species. Excess sleep, in  particular, is known ...

免疫与感染

High-Resolution Video Tracking of Locomotion in Adult Drosophila Melanogaster

Flies provide an important model for studying complex behavior due to the plethora of genetic tools available to researchers in this field. Studying locomotor behavior in Drosophila melanogaster relies on the ability to be able to quantify changes in motion during or in response to a given task. For this reason, a high-resolution video tracking system, such as the one we describe in this paper, is a valuable tool for measuring locomotion in real-time. Our protocol involves the use of an initial air pulse to break the flies momentum, followed by a thirty second filming period in a square chamber. A tracking program is then used to calculate the instantaneous speed of each fly within the chamber in 10 msec increments. Analysis software then compiles this data, and outputs a variety of parameters such as average speed, max speed, time spent in motion, acceleration, etc. This protocol will discuss proper feeding and management of flies for behavioral tasks, handling flies without anesthetization or immobilization, setting up a controlled environment, and running the assay from start to finish.

The study of complex locomotor behavior in Drosophila melanogaster is dependent upon the ability to quantify changes in a given fly's movement. This article demonstrates how to do this using a high-resolution tracking system.

高分辨率视频跟踪移动的，在成年果蝇。

Flies provide an important model for studying complex behavior due to the plethora of genetic tools available to researchers in this field.  Studying ...

生物学

A Screening Method for Identification of Heterochromatin-Promoting Drugs Using Drosophila

Drosophila is an excellent model organism that can be used to screen compounds that might be useful for cancer therapy. The method described here is a cost-effective in vivo method to identify heterochromatin-promoting compounds by using Drosophila. The Drosophila&#39;s DX1 strain, having a variegated eye color phenotype that reflects the extents of heterochromatin formation, thereby providing a tool for a heterochromatin-promoting drug screen. In this screening method, eye variegation is quantified based on the surface area of red pigmentation occupying parts of the eye and is scored on a scale from 1 to 5. The screening method is straightforward and sensitive and allows for testing compounds in vivo. Drug screening using this method provides a fast and inexpensive way for identifying heterochromatin-promoting drugs that could have beneficial effects in cancer therapeutics. Identifying compounds that promote the formation of heterochromatin could also lead to the discovery of epigenetic mechanisms of cancer development.

A Screening Method for Identification of Heterochromatin-Promoting Drugs Using Drosophila

Drosophila is a widely used experimental model suitable for screening drugs with potential applications for cancer therapy. Here, we describe the use of Drosophila variegated eye color phenotypes as a method for screening small-molecule compounds that promote heterochromatin formation.

使用果蝇的异色素促进药物的鉴定筛选方法

Drosophila is an excellent model organism that can be used to screen compounds that might be useful for cancer therapy. The method described here is a ...

High-Throughput Method for Measuring Alcohol Sedation Time of Individual Drosophila melanogaster

Drosophila melanogaster provides an excellent model to study the genetic underpinnings of alcohol sensitivity. In contrast to studies in human populations, the Drosophila model allows strict control over genetic background, and virtually unlimited numbers of individuals of the same genotype can be reared rapidly under well-controlled environmental conditions without regulatory restrictions and at relatively low cost. Flies exposed to ethanol undergo physiological and behavioral changes that resemble human alcohol intoxication, including loss of postural control, sedation, and development of tolerance. Here, we describe a simple, low-cost, high-throughput assay for assessing alcohol sedation sensitivity in large numbers of single flies. The assay is based on video recording of single flies introduced without anesthesia in 24-well cell culture plates in a set-up that enables synchronous initiation of alcohol exposure. The system enables a single person to collect individual ethanol sedation data on as many as 2,000 flies within an 8 h work period. The assay can, in principle, be extended to assess the effects of exposure to any volatile substance and applied to measure effects of acute toxicity of volatiles on other insects, including other fly species.

High-Throughput Method for Measuring Alcohol Sedation Time of Individual Drosophila melanogaster

Current methods to measure alcohol sensitivity in Drosophila are designed to test groups of flies. We present a simple, low-cost, high-throughput assay for assessing alcohol sedation sensitivity in large numbers of single flies. The method does not require specialized tools and can be performed in any laboratory using common materials.

测量个体果蝇黑色素气器酒精镇分时间的高通量方法

Drosophila melanogaster provides an excellent model to study the genetic underpinnings of alcohol sensitivity. In contrast to studies in human ...

行为学

A Simple Technique to Assay Locomotor Activity in Drosophila

Drosophila melanogaster is an ideal model organism for studying various diseases due to its abundance of advanced genetic manipulation techniques and diverse behavioral features. Identifying behavioral deficiency in animal models is a crucial measure of disease severity, for example, in neurodegenerative diseases where patients often experience impairments in motor function. However, with the availability of various systems to track and assess motor deficits in fly models, such as drug-treated or transgenic individuals, an economical and user-friendly system for precise evaluation from multiple angles is still lacking. A method based on the AnimalTracker application programming interface (API) is developed here, which is compatible with the Fiji image processing program, to systematically evaluate the movement activities of both adult and larval individuals from recorded video, thus allowing for the analysis of their tracking behavior. This method requires only a high-definition camera and a computer peripheral hardware integration to record and analyze behavior, making it an affordable and effective approach for screening fly models with transgenic or environmental behavioral deficiencies. Examples of behavioral tests using pharmacologically treated flies are given to show how the techniques can detect behavioral changes in both adult flies and larvae in a highly repeatable manner.

A Simple Technique to Assay Locomotor Activity in Drosophila

The present protocol assesses the locomotor activity of Drosophila by tracking and analyzing the movement of flies in a hand-made arena using open-source software Fiji, compatible with plugins to segment pixels of each frame based on high-definition video recording to calculate parameters of speed, distance, etc.

一种测定果蝇运动活性的简单技术

Drosophila melanogaster is an ideal model organism for studying various diseases due to its abundance of advanced genetic manipulation techniques and ...

An Inexpensive, Scalable Behavioral Assay for Measuring Ethanol Sedation Sensitivity and Rapid Tolerance in Drosophila

Alcohol use disorder (AUD) is a serious health challenge. Despite a large hereditary component to AUD, few genes have been unambiguously implicated in their etiology. The fruit fly, Drosophila melanogaster, is a powerful model for exploring molecular-genetic mechanisms underlying alcohol-related behaviors and therefore holds great promise for identifying and understanding the function of genes that influence AUD. The use of the Drosophila model for these types of studies depends on the availability of assays that reliably measure behavioral responses to ethanol. This report describes an assay suitable for assessing ethanol sensitivity and rapid tolerance in flies. Ethanol sensitivity measured in this assay is influenced by the volume and concentration of ethanol used, a variety of previously reported genetic manipulations, and also the length of time the flies are housed without food immediately prior to testing. In contrast, ethanol sensitivity measured in this assay is not affected by the vigor of fly handling, sex of the flies, and supplementation of growth medium with antibiotics or live yeast. Three different methods for quantitating ethanol sensitivity are described, all leading to essentially indistinguishable ethanol sensitivity results. The scalable nature of this assay, combined with its overall simplicity to set-up and relatively low expense, make it suitable for small and large scale genetic analysis of ethanol sensitivity and rapid tolerance in Drosophila.

An Inexpensive, Scalable Behavioral Assay for Measuring Ethanol Sedation Sensitivity and Rapid Tolerance in Drosophila

Straightforward assays for measuring ethanol sensitivity and rapid tolerance in Drosophila facilitate the use of this model organism for investigating these important ethanol-related behaviors. Here, a relatively simple, scalable assay for measuring ethanol sensitivity and rapid tolerance in flies is described.

一种廉价的，可扩展的行为分析测量乙醇镇静灵敏度和快速耐受<em&gt;果蝇</em

Alcohol use disorder (AUD) is a serious health challenge. Despite a large hereditary component to AUD, few genes have been unambiguously implicated in ...

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

Recently, egg-laying preference of Drosophila has emerged as a genetically tractable model to study the neural basis of simple decision-making processes. When selecting sites to deposit their eggs, female flies are capable of ranking the relative attractiveness of their options and choosing the &#34;greater of two goods.&#34; However, most egg-laying preference assays are not practical if one wants to take a systematic genetic screening approach to search for the circuit basis underlying this simple decision-making process, as they are population-based and laborious to set up. To increase the throughput of studying of egg-laying preferences of single females, we developed custom chambers that each can simultaneously assay egg-laying preferences of up to thirty individual flies as well as a protocol that ensures each female has a high egg-laying rate (so that their preference is readily discernable and more convincing). Our approach is simple to execute and produces very consistent results. Additionally, these chambers can be equipped with different attachments to allow video recording the egg-laying animals and to deliver light for optogenetics studies. This article provides the blueprints for fabricating these chambers and the procedure for preparing the flies to be assayed in these chambers.

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

This protocol describes a high throughput assay for testing egg-laying preferences of Drosophila melanogaster at single-animal resolution. This assay provides a simple, efficient, and scalable platform to identify genes and circuit components that control a simple decision-making process.

高通量检测，以检查个体产蛋首<em&gt;果蝇</em

Recently, egg-laying preference of Drosophila has emerged as a genetically tractable model to study the neural basis of simple decision-making processes. ...

使用黑腹果蝇对年龄相关睡眠障碍进行高通量小分子药物筛选

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此视频中的章节

含量自发活动，研究昼夜节律和睡眠参数果蝇

在Vivo前向遗传屏幕识别新的神经保护基因在果蝇黑色素

电检测屏幕的配对Nanoinjection和生物活性化合物的使用果蝇巨人纤维系统

定量测定的免疫反应和睡眠模式

高分辨率视频跟踪移动的，在成年果蝇。

使用果蝇的异色素促进药物的鉴定筛选方法

测量个体果蝇黑色素气器酒精镇分时间的高通量方法

一种测定果蝇运动活性的简单技术

一种廉价的，可扩展的行为分析测量乙醇镇静灵敏度和快速耐受

高通量检测，以检查个体产蛋首