我们承认维也纳的果蝇资源中心和布卢明顿果蝇股票中心 (NIH P40OD018537) 提供果蝇菌株。我们感谢 Klämbt 实验室介绍我们的岛屿化验和 Martijn Eidhof 建设的岛屿化验设置。这项研究的部分支持的 E-RARE-3 联合跨国调用赠款 "准备治疗常染色体隐性 ataxias" 准备 (NWO 9003037604), 由最高赠款 (912-12-109) 从荷兰科研组织 (NWO), 并由两 DCN/内梅亨大学医学中心博士研究生奖学金。资助者在研究设计、数据收集和分析、决定出版或准备原稿方面没有作用。

<ol>
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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Fly pushing: the theory and practice of Drosophila genetics. , (2004).</li><li>Rothblum-Oviatt, 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=Ataxia+telangiectasia:+a+review.">Ataxia telangiectasia: a review.</a> Orphanet J Rare Dis. 11, 159 (2016).</li><li>Petersen, A. J., Rimkus, S. A., Wassarman, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATM+kinase+inhibition+in+glial+cells+activates+the+innate+immune+response+and+causes+neurodegeneration+in+Drosophila.">ATM kinase inhibition in glial cells activates the innate immune response and causes neurodegeneration in Drosophila.</a> Proc Natl Acad Sci U S A. 109, E656-E664 (2012).</li><li>Gargano, J. W., Martin, I., Bhandari, P., Grotewiel, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+iterative+negative+geotaxis+(RING):+a+new+method+for+assessing+age-related+locomotor+decline+in+Drosophila.">Rapid iterative negative geotaxis (RING): a new method for assessing age-related locomotor decline in Drosophila.</a> Exp Gerontol. 40, 386-395 (2005).</li><li>. ImageJ User Guide - IJ 1.46 Available from: <a target="_blank" href="https://imagej.nih.gov/ij/docs/guide/146-30.html">https://imagej.nih.gov/ij/docs/guide/146-30.html</a> (2012)</li></ol>

作者没有利益冲突透露。

该协议描述了 "果蝇岛检测" 宏, 它定量地评估了在岛试验期间的果蝇马达行为。该宏精确地计算了平台上的苍蝇, 使得该岛检测高度敏感, 适合于定量高通量的运动缺陷评估。该方法可以比较任何条件, 苍蝇生长在不同的遗传和/或环境条件, 包括药物接触。因此, 在研究果蝇运动障碍和其他神经系统疾病的模型时, 或者当检查移动或飞行时, 这种读数在执行大型基因或药物屏幕时特别有用。行为.
这份手稿中提出的岛屿化验协议比现有的/替代的方法具有优势。例如, 视频跟踪移动是非常耗时, 更不适合测试大样本大小。海岛试验是高通量的筛选工具, 并且, 从这个意义上, 是可比较的快速交互式消极 geotaxis (圆环) 试验16。两者之间的区别在于, 该岛的化验可以检测出更广泛的运动问题;苍蝇无法离开平台, 可能是由机翼 (肌肉/神经) 和/或腿部 (肌肉/神经) 缺陷引起的飞行、跳跃或行走行为的缺陷造成的。另一方面, 环法评估腿 (肌肉/神经) 缺陷引起的攀爬/行走行为的缺陷。如果用户有兴趣在多个行为读数, 海岛分析也可以很容易地结合其他的化验, 如环化验。此外, 遗传学所需的激光器可以很容易地安装在岛形试验箱中, 安装非常简单, 可以方便地移动到温度和光线可以控制的房间。
为了确保在这里描述的海岛试验的成功和重现性, 应遵循若干建议。在实验前至少一天将苍蝇分和转移到实验测试瓶中, 以避免 CO2或冷麻醉的影响。不要拥挤实验用的小瓶 (每瓶 10-15 只苍蝇; 最好总是每瓶放相同数量的苍蝇)。时刻保持新鲜食物的苍蝇。如果还不熟悉进行化验, 练习投掷飞到平台上, 以最大限度地提高产量。同时练习快速缩回手, 因为它干扰数据分析 (图象分析和飞行计数开始, 在手是从图片以后)。在需要比较的实验中保持环境和实验条件相同 (例如,控件与突变体或不同年龄段的基因型测试)。始终在当天的同一时间进行实验, 并在控制温度和湿度条件下保持小瓶。对于统计能力, 测试每生物复制至少三技术复制。
为了确保此处描述的宏的成功性能, 必须调整网络摄像头和图像设置以达到最大的对比度: 在白色平台上, 苍蝇出现在黑色物体上。当宏数未正确计算时, 请调整对比度设置, 检查是否正确选择了 ROI, 并确保平台上的苍蝇大小高于指定的最小飞行大小设置 (请参见本协议的步骤 8.3)。这些设置只需要定义一次。它们适用于所有的实验, 只要摄像头和平台之间的距离不变。Circularity_min 和最大设置定义了粒子的循环 (粒子 = 计数苍蝇), 将被考虑到分析 (苍蝇 = 计数的对象)。1代表一个完美的圆圈, 0 代表一行17。由于苍蝇总是存在一定程度的循环 (苍蝇不能显示为直线), "Circularity_max" 设置设置为 1, "Circularity_min" 设置设置为0.4。用户不太可能需要调整这些设置。
当一只苍蝇靠近站台的边界时, 这个宏偶尔会计算错误。这可能发生, 如果苍蝇不能飞, 但进出用户定义的 ROI。在大多数情况下, 重新的 ROI (尽可能多地安装到平台) 可以很容易地解决此问题。然而, "海岛分析" 脚本能够检测和纠正不正确的数据计数由苍蝇进出的 ROI 比较好。虽然在这里提出的摄像头的分辨率很高, 足以辨别苍蝇在接近接近相当好, 我们已经实现了额外的算法在图像处理过程中的 "果蝇岛检测" 宏, 如分水岭和侵蚀功能17。这些便利了在平台上接近的苍蝇的正确划定。此外, 宏无法区分从平台上跳过的苍蝇, 也无法将其从站台上飞离. 尽管如此, 人们普遍认为, 健康的幼蝇在跌落到平台上时会立即飞走, 而老年苍蝇和有运动缺陷的苍蝇在站台上停留的时间更长, 最终会从平台上跳跃或脱落。尽管有这些限制, 化验和分析提供了一个非常精确的运动行为的测量。
为了确保 "岛屿分析" 脚本的成功执行, 用户必须确保在协议中指示的脚本行中输入正确的输入和输出文件路径, 并以正确的文件夹格式提供数据 (如在图 2中)。如果用户发现用于筛选出不可靠的实验数据的条件太严格 (68 行: "count" 列中的第一个值小于或等于 5; 行 71: "count" 列中的第一个值高于平台上抛出的苍蝇总数rm + 3), 通过在 "岛分析" 脚本中的68和71行中的文本前面添加 # 来关闭这些筛选器设置。在这种情况下, 所有数据集都将包括在分析中。或者, 可以通过根据用户需要调整68和71行中的值来更改筛选器设置。"果蝇" 分析宏生成的 "results.txt" 中的计数值中可能的工件也可以手动调整, 并且可以在调整后的数据上重新运行脚本。当用户有兴趣处理超过 10 fps, 或超过十年代的数据, 由 "岛屿分析" 脚本处理的帧数应进行调整。统计分析也可以被用户定义的替代品取代。
一个名为 "示例岛分析" 的文件夹, 包含了使用岛分析获得的图像时间序列的示例, 可以在以下网站中找到: https://doi-org.remotexs.ntu.edu.sg/10.6084/m9.figshare.4309652.v1。下载 "示例岛分析" 文件夹, 并按照本协议中描述的步骤快速熟悉文件存储的结构, 用 "果蝇岛检测" 宏处理图像, 并对 "岛屿检测"脚本.
海岛化验, 结合发达的宏观和分析脚本, 可用于评估和量化的异常运动行为的一个果蝇模型的共济失调-扩张。由于该方法可以有效地应用于不同年龄段, 因此很适合于分析表型的潜在渐进性。
总之, 海岛化验, 结合 "果蝇岛试验" 的宏观和 "岛屿分析" 的脚本, 是一个 cost-effective, 可靠, 高效的分析和量化的运动缺陷的果蝇以高通量的方式运动障碍模型。

近年来, 下一代测序技术的进展, 极大地促进了对大脑退行性运动障碍 (例如,小脑共济失调和帕金森) 的基因的识别, 这是外周神经元起源 (例如,肌萎缩侧索硬化症和遗传性痉挛性截瘫) 和肌肉来源 (如,杜氏肌营养不良症和强直营养不良)1234.尽管如此, 对于大多数这些疾病的分子机制, 人们还是知之甚少。更好地了解这些机制对于发展治疗是必不可少的。
与人类一样, 模型生物体的运动, 如在果蝇中的飞行和移动, 是由中央大脑、周围神经系统和肌肉控制的。此外, 快速的世代时间和遗传工具箱的果蝇使这个模型有机体特别适合高通量筛选的基因涉及运动障碍和药物测试5,6.由于大量的条件需要在这样的屏幕上测试, 可靠, cost-effective, 和相对简单的化验, 以及工具, 以自动的方式量化输出结果, 是非常可取的。
施密特et al.(2012)7描述了一个名为 "岛屿检测" 的低成本测试, 以评估果蝇的运动行为。该岛的检测已成功地用于 large-scale 筛查, 以确定具有胶质细胞特异功能的基因7, 在评估果蝇模型的智力残疾8, 并为一般评价飞行马达行为9。该岛试验的原理设计包括一个高架平台上, 其中几个苍蝇抛出。这导致了一种先天的运动行为, 使健康的苍蝇能够在几秒钟内从平台上逃脱。该检测方法测量在平台上剩余的苍蝇数量7,8,9。所有这些特征表明, 海岛检测可能是一个强有力的筛选工具的基因参与运动障碍。
目前, 对拍摄的岛试验数据进行定量分析的方法是手动7,8,9。为了提高检测的效率, 开发了一种低成本的半自动定量的方法。安装使用一个简单的摄像头连接到一台笔记本电脑收集的图像时间序列的平台, 与帧获得每0.1 秒. 然后用 "果蝇岛检测" 宏来处理平台上的苍蝇数量时间."果蝇岛检测" 宏分为三独立 sub-macros: (I) "创建堆栈和投影", sub-macro 标识不同子文件夹中存储的各种岛实验, 并创建一个堆栈和每个时间序列。(二) "定义平台" sub-macro 将连续打开位于单个实验子文件夹中的所有 "Projection_image_name. tif" 文件, 此时用户被要求手动将岛平台定义为感兴趣的区域 (ROI)。(三) "分析" 在时间序列中自动量化在平台上剩余的苍蝇数量。sub-macros 可以连续运行 (在一个运行) 或独立。对于统计数据分析, 编写了一个脚本来自动处理所获得的数据, 并应用统计测试来确定治疗/基因型的行为是否有明显的不同 (图 1)。最后, 证明了这种设置可以用来评估和量化的异常运动能力的果蝇模型的共济失调-扩张 (AT)。

<table>
	<tbody>
		<tr>
			<td class="xl19">25 x 95 mm Drosophila vials</td>
			<td class="xl19">Flystuff</td>
			<td class="xl20">32-116SB</td>
			<td class="xl19">-</td>
		</tr>
		<tr>
			<td class="xl21">Logitech C525 HD Webcam</td>
			<td class="xl19">Logitech</td>
			<td class="xl19">-</td>
			<td class="xl19">Any webcam with USB connection is suitable.</td>
		</tr>
		<tr>
			<td class="xl19">Stand to hold webcam</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
		</tr>
		<tr>
			<td class="xl19">Lamp</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">12 V LED lights are appropriate</td>
		</tr>
		<tr>
			<td class="xl19">Pounding pad</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Any mouse pad works</td>
		</tr>
		<tr>
			<td class="xl19">Island Assay box</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Dimensions 40x35x2.5 cm. Hole 20x30 cm. Transparent.</td>
		</tr>
		<tr>
			<td class="xl19">Island Assay bath</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Dimensions 42x38x25 cm. Non white.</td>
		</tr>
		<tr>
			<td class="xl19">Island/platform</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Dimensions 42x38x25 cm. Uniform white.</td>
		</tr>
		<tr>
			<td class="xl19">Soap</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Standard dishwashing detergent is suitable.</td>
		</tr>
		<tr>
			<td class="xl19">Computer</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Scripts run both on Windows and Mac</td>
		</tr>
		<tr>
			<td class="xl22">Image-recording software: HandiAvi&#174;</td>
			<td class="xl23">AZcendant&#174;</td>
			<td class="xl23">-</td>
			<td class="xl19">HandyAvi is only compatible with Windows and has been described throughout the manuscript. It can be downloaded from: http://www.azcendant.com/DownloadHandyAvi.html (version 5.0)</td>
		</tr>
		<tr>
			<td class="xl22">Image-recording software: WebcamCapture</td>
			<td class="xl25">-</td>
			<td class="xl25">-</td>
			<td class="xl25">Fiji/ImageJ plugin that can be used on Mac alternative to HandyAvi for image-recordings and can be downloaded from: https://imagej.nih.gov/ij/plugins/webcam-capture/ When using this method, the user has to use the same folder setup and image-recording settings indicated in this manuscript, with the exception that for each experimental replicate, the captured image stack should be exported as Stack.tiff to the corresponding experimental replicate folder. Upon running the &#34;Drosophila Island Assay&#34; macro on this data, no text should be present in the &#34;First frame identifier&#34; setting.</td>
		</tr>
		<tr>
			<td class="xl19">Fiji</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl19">Version 1.4 or higher, can be downloaded from: https://figshare.com/s/def4197ee0010b21a76f</td>
		</tr>
		<tr>
			<td class="xl19">R studio</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl24">Can be downloaded from: https://www.rstudio.com/products/rstudio/download/</td>
		</tr>
		<tr>
			<td class="xl19">R</td>
			<td class="xl19">-</td>
			<td class="xl19">-</td>
			<td class="xl24">Version 3.3.2, can be downloaded from: https://cran.rstudio.com</td>
		</tr>
	</tbody>
</table>

high-throughput analysis of locomotor behavior in the drosophila island assay

下一代测序技术的进展有助于识别 (候选) 疾病基因的运动障碍和其他神经系统疾病以越来越快的速度。然而, 对于这些疾病的分子机制, 却知之甚少。果蝇的遗传、分子和行为工具箱使这种模型生物体特别有用, 以高通量的方式表征新的疾病基因和机制。然而, 高通量的屏幕需要有效和可靠的化验, 理想情况下, 是 cost-effective, 并允许自动化量化的特点与这些疾病有关。海岛试验是一种 cost-effective 和容易地设置方法评估果蝇运动行为。在这个试验中, 苍蝇被抛到一个固定高度的平台上。这就产生了一种固有的马达反应, 使苍蝇能够在几秒钟内从平台上逃生。目前, 对拍摄的岛屿化验进行定量分析是手工进行的, 这是一项费力的工作, 特别是在执行大屏幕时。
这份手稿描述了 "果蝇岛检测" 和 "岛屿分析" 算法的高通量, 自动化数据处理和量化的岛屿化验数据。在安装过程中, 连接到膝上型计算机的简单摄像头在执行检测时收集平台的图像系列。为开源软件开发的 "果蝇岛试验" 算法斐济处理这些图像系列和量化, 为每个实验条件, 在平台上的苍蝇数量随着时间的推移。"海岛分析" 剧本, 与自由软件 R 兼容, 被开发了自动地处理获取的数据和计算治疗或基因型是否统计地不同。这极大地提高了岛上试验的效率, 使其成为基本运动和飞行行为的有力的读数。因此, 它可以应用于大屏幕调查飞行活动能力,果蝇模型的运动障碍, 和药物的功效。

在所描述的协议中,果蝇岛分析数据是通过三步骤获取和处理的。首先, 在岛平台上抛出的果蝇的逃跑响应被记录在一个摄像头上, 并作为个人. bmp 图像 (协议节 1-7)。其次, "果蝇岛检测" 宏 (步骤 8) 处理帧, 生成 "result.txt" 文本文件(表 1), 其中对每个帧中检测到的对象数进行汇总, 并显示一个图像堆栈 "Result_stack. tiff", 这表明在每个框架的平台区域内检测到的对象。第三, "岛屿化验分析" 脚本 (协议9节) 处理存储在 "results.txt" 文件中的单个实验的宏数据。脚本中包含了几个步骤来筛选和合并数据以进行统计分析。在平台上抛出苍蝇的第一帧被检测到并被认为是时间点1。早期的帧从数据集中被删除。100帧跟随时间点 1 (对应于十年代) 被选择为分析。实验中, 在平台上检测到的初始数量小于5的苍蝇被自动排除在分析之外, 从而消除了不可靠的实验结果。试验中, 在平台上检测到的苍蝇的初始数量超过了 "每瓶苍蝇数" 的设置加上3的耐受性。这消除了噪声粒子被错误地检测为苍蝇的数据集。然后, 该脚本将计算每个时间点检测到的苍蝇的百分比, 与该系列中检测到的最高数量的苍蝇相比。由苍蝇进出 ROI 引起的数据集中的错误 (随着时间的推移被检测为减少, 然后在平台上飞行的百分比增加) 会自动更正为在平台上始终存在的早期阶段.在主目录中存在的特定实验条件的所有复制数据集都被合并并导出到 "data_all_conditions. csv" 文件中。它的列表示表 2中描述的变量。该脚本还将导出每个实验条件的折线图, 根据包含数据的文件夹命名。此图显示了在相应的文件夹(图 3A-b)中存在的试验性复制在平台上剩余的飞行百分比 (逃跑响应)。在 "统计摘要. csv" 文件中计算并总结了每个实验条件的平均值、SD 和 SEM。一个名为 "Escape_response_all_conditions. tiff" 的折线图显示了在主文件夹(图 3C)中存在多达12实验条件的平均飞行逃生响应。最后, 在 "联合自卫队. csv" 文件中计算并总结了在主文件夹中存在的所有实验条件下曲线的面积。根据主文件夹中存在的条件数, 脚本要么执行两尾不配对的韦尔奇 t 检验 (2 条件), 要么进行多项测试的 Tukey 校正 (超过2条件), 以确定是否实验条件不同。这些结果在 "Welch_t-test_results. txt" 或 "AUC_anova_results" 中总结。在执行方差分析时, 该脚本还将导出 "AUC_anova. tiff" 文件, 以显示平均联合自卫队的差异和所比较的实验条件的95% 置信区间。所有实验条件下, 实验复制曲线下绝对区域的值显示为 "中线" (图 3D) 中的单个数据点。
共济失调扩张 (AT) 是一种常染色体隐性运动障碍的特点是早期发作小脑共济失调由于突变的共济失调扩张突变 (ATM) 基因14。ATM的果蝇orthologue 的变种, tefu, 显示移动性和长寿性缺陷15。为了评估 "果蝇岛检测" 宏, 在岛试验中测试了一个果蝇模型, 并将宏的数据输出与手动数据计数进行了比较。结果表明, 无处不在的tefu击倒 (w -;Actin-Gal4/GD11950) 与它们的遗传背景控件相比, 大大降低了这些苍蝇离开平台的能力 (w -;Actin-Gal4/+) (图 4).1秒后, 50% 的控制苍蝇逃脱了平台, 相比之下, #60; 1% 的tefu-rna 干扰飞。重要的是, 用宏获得的数据忠实地再现了通过手工计数获得的数据, 表明该宏是一种可靠的工具, 可用于定量分析岛屿化验数据和评估移动缺陷(图 4A-b)。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55892/55892fig1.jpg"> 
图 1: 流程图概述了岛屿试验的要求、试验过程和分析.(A) 海岛化验设备。(B) 试验性设置为海岛化验。(C) 海岛化验。(D) 使用 "果蝇岛检测" 宏处理海岛化验数据。"果蝇岛检测" 宏由 3 sub-macros: 1) 进行叠加和投影, 2) 定义平台和 3) 分析。(E) 使用 "岛屿化验分析" 脚本对数据进行处理和统计评估。<a href="//ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55892/55892fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55892/55892fig2.jpg"> 
图 2: 在协议中需要进行不同调整的示例.(A) 所需的目录结构, 其中必须为数据处理和分析而存储岛屿化验实验。(B) 在调整视频设置时, 白色背景上的苍蝇必须呈黑色。(C) 图像帧输出文件由本手稿中描述的图像记录软件保存。(D) 黄色轮廓显示平台选择。"ROI 管理器" 中的存储平台选择以蓝色突出显示。(E) 在调整 "最小飞行大小" 设置期间, 苍蝇被表示为白色圆点。结果窗口以像素为单位显示苍蝇的面积。(F) 示例中的单个记录的图像帧 (在左侧) 和相应的帧在生成的图像堆栈中, 获得与 "果蝇岛检测" 宏 (在右边)。<a href="//ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55892/55892fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55892/55892fig3.jpg"> 
图 3: 通过 "岛分析" 脚本进行数据处理后获得的结果图像.(A) 折线图, 显示每个控制实验复制的逃跑响应。(B) 折线图显示每个 tefu 的 rna 干扰实验复制的逃跑响应。(C) 所示实验条件的平均飞行逃逸响应;误差线代表 SEM. (D) 点图表示控制和突变条件下的曲线分布区域。tefu rna 干扰和控制条件的实验复制显示为单独的数据点 (黑色) 与中线 (红线)。<a href="//ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55892/55892fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55892/55892fig4.jpg"> 
图 4: 无处不在的tefu击倒苍蝇显示出离开平台的能力明显下降。数据表示平台上的飞行百分比 (以时间为控制) (w-;Actin-Gal4/+) 和 tefu rna 干扰 (w-;Actin-Gal4/GD11950) 苍蝇。(复制次数 = 5; 误差线表示 SEM)。(A) 通过 "果蝇岛检测" 宏获得的原始数据。(B) 点图表示在 "果蝇岛检测" 宏 (韦尔奇不成对 t 检验, ** 和 #60 0.01) 中获得的控制和 tefu 干扰条件下的曲线分布区域。(C) 通过手动计算每秒岛上存在的苍蝇数量获得的原始数据。(D) 点图代表在曲线分布下的区域控制和 Tefu 的干扰条件, 由手工计数 (韦尔奇不成对 t 检验, ** 和 #60; 0.01)。误差线代表 SEM.<a href="//ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55892/55892fig4large.jpg" target="_blank">请单击此处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>列名</td>
			<td colspan="3">描述</td>
		</tr>
		<tr>
			<td>切片</td>
			<td colspan="3">帧名称。</td>
		</tr>
		<tr>
			<td>数</td>
			<td colspan="3">在平台范围内检测到的对象数 (ROI)。</td>
		</tr>
		<tr>
			<td>总面积</td>
			<td colspan="3">在平台 (ROI) 范围内的框架中检测到的对象的总面积 (以像素为单位)。</td>
		</tr>
		<tr>
			<td>平均尺寸</td>
			<td colspan="3">在框架中检测到的对象的总面积除以平台范围内的对象数 (ROI)。</td>
		</tr>
		<tr>
			<td>% 区域</td>
			<td colspan="3">相对于平台总面积 (ROI) 的对象所占面积的百分比。</td>
		</tr>
		<tr>
			<td>Perim</td>
			<td colspan="3">在平台 (ROI) 范围内的框架中检测到的对象的总周长 (以像素为单位)。</td>
		</tr>
		<tr>
			<td>最小飞码</td>
			<td colspan="3">用户在 "果蝇岛检测" 宏的图形界面中定义的最小飞行大小设置 (以像素为单位)。</td>
		</tr>
		<tr>
			<td>区域 ROI</td>
			<td colspan="3">用户在运行 sub-macro 定义平台 (以像素为单位) 期间定义的平台区域 (ROI)。</td>
		</tr>
		<tr>
			<td>苍蝇数量</td>
			<td colspan="3">用户在 "果蝇岛检测" 宏的图形界面中定义的每个实验使用的苍蝇数量。</td>
		</tr>
	</tbody>
</table>
表 1: 由 "果蝇岛检测" 宏测量的参数。运行 "果蝇岛检测" 宏时, 此表中描述的参数将出现在 "results.txt" 文件中。
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>列名</td>
			<td colspan="3">描述</td>
		</tr>
		<tr>
			<td>切片</td>
			<td colspan="3">帧数。</td>
		</tr>
		<tr>
			<td>数</td>
			<td colspan="3">在平台范围内检测到的苍蝇数量 (ROI)。</td>
		</tr>
		<tr>
			<td>十. 区域</td>
			<td colspan="3">在平台 (ROI) 范围内的帧中检测到的苍蝇的总面积 (以像素为单位)。</td>
		</tr>
		<tr>
			<td>最小飞码</td>
			<td colspan="3">用户在 "果蝇岛检测" 宏 (以像素为单位) 的图形界面中定义的最小飞行大小条目设置。</td>
		</tr>
		<tr>
			<td>区域 ROI</td>
			<td colspan="3">用户在运行 sub-macro "定义平台" 时定义的平台区域 (ROI, 以像素为单位)。</td>
		</tr>
		<tr>
			<td>苍蝇数量</td>
			<td colspan="3">用户在 "果蝇岛检测" 宏的图形界面中定义的每个实验使用的苍蝇数量。</td>
		</tr>
		<tr>
			<td>十. 计数</td>
			<td colspan="3">在试验台上, 相对于平台上检测到的最高数量的苍蝇, 在平台上存在的苍蝇的百分比。</td>
		</tr>
		<tr>
			<td>Timepoint</td>
			<td colspan="3">时间点1表示要分析的第一帧, 对应于在平台上首次出现苍蝇的帧。在使用所描述的设置时, 每个复制分析都有100帧 (对应于十年代。</td>
		</tr>
		<tr>
			<td>实验</td>
			<td colspan="3">每个条件的复制数。</td>
		</tr>
		<tr>
			<td>条件</td>
			<td colspan="3">指示实验条件的名称 (根据包含数据的文件夹的用户定义名称)。</td>
		</tr>
	</tbody>
</table>
表 2: 使用 "岛分析" 脚本处理数据后所获得的变量的描述.该表中描述的参数显示在 "data_all_conditions. csv" 文件中, 处理数据时使用 "岛分析" 脚本。

Watch this Scientific Journal Video about High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay at JoVE.com

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

海岛试验是一种比较新的, cost-effective 的方法, 可用于评估的基本运动行为的果蝇。这份手稿描述了自动数据处理的算法和岛屿试验数据的客观量化, 使得这种方法成为一个敏感的高通量的大基因或药理屏幕的读数。

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 ...

high-throughput-analysis-locomotor-behavior-drosophila-island

Nanyang Technological University

Research

JoVE Journal

Neuroscience

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

8.8K 次观看.  Radboud University Medical Center. 海岛试验是一种比较新的, cost-effective 的方法, 可用于评估的基本运动行为的果蝇。这份手稿描述了自动数据处理的算法和岛屿试验数据的客观量化, 使得这种方法成为一个敏感的高通量的大基因或药理屏幕的读数。

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

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed in sensory hairs called sensilla, which cover the surface of olfactory organs. The surface of each sensillum is covered with tiny pores, through which odorants pass and dissolve in a fluid called sensillum lymph, which bathes the sensory dendrites of the OSNs housed in a given sensillum. The OSN dendrites express odorant receptor (OR) proteins, which in insects function as odor-gated ion channels4, 5. The interaction of odorants with ORs either increases or decreases the basal firing rate of the OSN. This neuronal activity in the form of action potentials embodies the first representation of the quality, intensity, and temporal characteristics of the odorant6, 7.
Given the easy access to these sensory hairs, it is possible to perform extracellular recordings from single OSNs by introducing a recording electrode into the sensillum lymph, while the reference electrode is placed in the lymph of the eye or body of the insect. In Drosophila, sensilla house between one and four OSNs, but each OSN typically displays a characteristic spike amplitude. Spike sorting techniques make it possible to assign spiking responses to individual OSNs. This single sensillum recording (SSR) technique monitors the difference in potential between the sensillum lymph and the reference electrode as electrical spikes that are generated by the receptor activity on OSNs1, 2, 8. Changes in the number of spikes in response to the odorant represent the cellular basis of odor coding in insects. Here, we describe the preparation method currently used in our lab to perform SSR on Drosophila melanogaster and Anopheles gambiae, and show representative traces induced by the odorants in a sensillum-specific manner.

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

Electrophysiological responses of olfactory sensory neurons to odorants can be measured in insects using single sensillum recordings. In this video article we will demonstrate how to perform single sensillum recordings in the antennae of the vinegar fly (Drosophila melanogaster) and the maxillary palps of the malaria mosquito (Anopheles gambiae).

在昆虫单感器记录果蝇按蚊</em

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed ...

科研

神经科学

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 ...

Studying the Neural Basis of Adaptive Locomotor Behavior in Insects

Studying the neural basis of walking behavior, one often faces the problem that it is hard to separate the neuronally produced stepping output from those leg movements that result from passive forces and interactions with other legs through the common contact with the substrate. If we want to understand, which part of a given movement is produced by nervous system motor output, kinematic analysis of stepping movements, therefore, needs to be complemented with electrophysiological recordings of motor activity. The recording of neuronal or muscular activity in a behaving animal is often limited by the electrophysiological equipment which can constrain the animal in its ability to move with as many degrees of freedom as possible. This can either be avoided by using implantable electrodes and then having the animal move on a long tether (i.e. Clarac et al., 1987; Duch &amp; Pfl&uuml;ger, 1995; B&ouml;hm et al., 1997; Gruhn &amp; Rathmayer, 2002) or by transmitting the data using telemetric devices (Kutsch et al, 1993; Fischer et al., 1996; Tsuchida et al. 2004; Hama et al., 2007; Wang et al., 2008). Both of these elegant methods, which are successfully used in larger arthropods, often prove difficult to apply in smaller walking insects which either easily get entangled in the long tether or are hindered by the weight of the telemetric device and its batteries. In addition, in all these cases, it is still impossible to distinguish between the purely neuronal basis of locomotion and the effects exerted by mechanical coupling between the walking legs through the substrate. One solution for this problem is to conduct the experiments in a tethered animal that is free to walk in place and that is locally suspended, for example over a slippery surface, which effectively removes most ground contact mechanics. This has been used to study escape responses (Camhi and Nolen, 1981; Camhi and Levy, 1988), turning (Tryba and Ritzman, 2000a,b; Gruhn et al., 2009a), backward walking (Graham and Epstein, 1985) or changes in velocity (Gruhn et al., 2009b) and it allows the experimenter easily to combine intra- and extracellular physiology with kinematic analyses (Gruhn et al., 2006).
We use a slippery surface setup to investigate the timing of leg muscles in the behaving stick insect with respect to touch-down and lift-off under different behavioral paradigms such as straight forward and curved walking in intact and reduced preparations.

We describe a method to record motor activity, timed to the electrically recorded tarsal contact signal in a tethered insect, walking on a slippery surface. This is used to study the neural basis of adaptive behavior under reduced influence of mechanical interaction between legs through the substrate.

研究昆虫的自适应运动能力行为的神经基础

Studying the neural basis of walking behavior, one often faces the problem that it is hard to separate the neuronally produced stepping output from those ...

In vivo Electroporation of Developing Mouse Retina

The functional characterization of genes expressed during mammalian retinal development remains a significant challenge. Gene targeting to generate constitutive or conditional loss of function knockouts remains cost and labor intensive, as well as time consuming. Adding to these challenges, retina expressed genes may have essential roles outside the retina leading to unintended confounds when using a knockout approach. Furthermore, the ability to ectopically express a gene in a gain of function experiment can be extremely valuable when attempting to identify a role in cell fate specification and/or terminal differentiation.
We present a method for the rapid and efficient incorporation of DNA plasmids into the neonatal mouse retina by electroporation. The application of short electrical impulses above a certain field strength results in a transient increase in plasma membrane permeability, facilitating the transfer of material across the membrane 1,2,3,4. Groundbreaking work demonstrated that electroporation could be utilized as a method of gene transfer into mammalian cells by inducing the formation of hydrophilic plasma membrane pores allowing the passage of highly charged DNA through the lipid bilayer 5. Continuous technical development has resulted in the viability of electroporation as a method for in vivo gene transfer in multiple mouse tissues including the retina, the method for which is described herein 6, 7, 8, 9, 10. 
DNA solution is injected into the subretinal space so that DNA is placed between the retinal pigmented epithelium and retina of the neonatal (P0) mouse and electrical pulses are applied using a tweezer electrode. The lateral placement of the eyes in the mouse allows for the easy orientation of the tweezer electrode to the necessary negative pole-DNA-retina-positive pole alignment. Extensive incorporation and expression of transferred genes can be identified by postnatal day 2 (P2). Due to the lack of significant lateral migration of cells in the retina, electroporated and non-electroporated regions are generated. Non-electroporated regions may serve as internal histological controls where appropriate. 
Retinal electroporation can be used to express a gene under a ubiquitous promoter, such as CAG, or to disrupt gene function using shRNA constructs or Cre-recombinase. More targeted expression can be achieved by designing constructs with cell specific gene promoters. Visualization of electroporated cells is achieved using bicistronic constructs expressing GFP or by co-electroporating a GFP expression construct. Furthermore, multiple constructs may be electroporated for the study of combinatorial gene effects or simultaneous gain and loss of function of different genes. Retinal electroporation may also be utilized for the analysis of genomic cis-regulatory elements by generating appropriate expression constructs and deletion mutants. Such experiments can be used to identify cis-regulatory regions sufficient or required for cell specific gene expression 11. Potential experiments are limited only by construct availability.

In vivo Electroporation of Developing Mouse Retina

A method for the incorporation of plasmid DNA into murine retinal cells for the purpose of performing either gain- or loss of function studies in vivo is presented. This method capitalizes on the transient increase in permeability of cell plasma membranes induced by the application of an external electrical field.

在发展中国家小鼠视网膜体内电穿孔

The functional characterization of genes expressed during mammalian retinal development remains a significant challenge.  Gene targeting to generate ...

Methods to Assay Drosophila Behavior

Drosophila melanogaster, the fruit fly, has been used to study molecular mechanisms of a wide range of human diseases such as cancer, cardiovascular disease and various neurological diseases1. We have optimized simple and robust behavioral assays for determining larval locomotion, adult climbing ability (RING assay), and courtship behaviors of Drosophila. These behavioral assays are widely applicable for studying the role of genetic and environmental factors on fly behavior. Larval crawling ability can be reliably used for determining early stage changes in the crawling abilities of Drosophila larvae and also for examining effect of drugs or human disease genes (in transgenic flies) on their locomotion. The larval crawling assay becomes more applicable if expression or abolition of a gene causes lethality in pupal or adult stages, as these flies do not survive to adulthood where they otherwise could be assessed. This basic assay can also be used in conjunction with bright light or stress to examine additional behavioral responses in Drosophila larvae. Courtship behavior has been widely used to investigate genetic basis of sexual behavior, and can also be used to examine activity and coordination, as well as learning and memory. Drosophila courtship behavior involves the exchange of various sensory stimuli including visual, auditory, and chemosensory signals between males and females that lead to a complex series of well characterized motor behaviors culminating in successful copulation. Traditional adult climbing assays (negative geotaxis) are tedious, labor intensive, and time consuming, with significant variation between different trials2-4. The rapid iterative negative geotaxis (RING) assay5 has many advantages over more widely employed protocols, providing a reproducible, sensitive, and high throughput approach to quantify adult locomotor and negative geotaxis behaviors. In the RING assay, several genotypes or drug treatments can be tested simultaneously using large number of animals, with the high-throughput approach making it more amenable for screening experiments.

Methods to Assay Drosophila Behavior

Drosophila melanogaster is a genetically and behaviorally tractable model system that has been used to understand the molecular and cellular basis of many important biological processes for over a century 1. Drosophila has been well exploited to gain insights into the genetic basis of fly behavior.

对检测方法果蝇行为

Drosophila melanogaster, the fruit fly, has been used to study molecular mechanisms of a wide range of human diseases such as cancer, cardiovascular ...

Optogenetic Stimulation of Escape Behavior in Drosophila melanogaster

A growing number of genetically encoded tools are becoming available that allow non-invasive manipulation of the neural activity of specific neurons in Drosophila melanogaster1. Chief among these are optogenetic tools, which enable the activation or silencing of specific neurons in the intact and freely moving animal using bright light. Channelrhodopsin (ChR2) is a light-activated cation channel that, when activated by blue light, causes depolarization of neurons that express it. ChR2 has been effective for identifying neurons critical for specific behaviors, such as CO2 avoidance, proboscis extension and giant-fiber mediated startle response2-4. However, as the intense light sources used to stimulate ChR2 also stimulate photoreceptors, these optogenetic techniques have not previously been used in the visual system. Here, we combine an optogenetic approach with a mutation that impairs phototransduction to demonstrate that activation of a cluster of loom-sensitive neurons in the fly's optic lobe, Foma-1 neurons, can drive an escape behavior used to avoid collision. We used a null allele of a critical component of the phototransduction cascade, phospholipase C-&beta;, encoded by the norpA gene, to render the flies blind and also use the Gal4-UAS transcriptional activator system to drive expression of ChR2 in the Foma-1 neurons. Individual flies are placed on a small platform surrounded by blue LEDs. When the LEDs are illuminated, the flies quickly take-off into flight, in a manner similar to visually driven loom-escape behavior. We believe that this technique can be easily adapted to examine other behaviors in freely moving flies.

Optogenetic Stimulation of Escape Behavior in Drosophila melanogaster

Genetically encoded optogenetic tools enable noninvasive manipulation of specific neurons in the Drosophila brain. Such tools can identify neurons whose activation is sufficient to elicit or suppress particular behaviors. Here we present a method for activating Channelrhodopsin2 that is expressed in targeted neurons in freely walking flies.

Optogenetic刺激的逃避行为<em&gt;果蝇</em

A  growing number of genetically encoded tools are becoming available that allow non-invasive  manipulation of the neural activity of specific neurons in ...

A Single-fly Assay for Foraging Behavior in Drosophila

For many animals, hunger promotes changes in the olfactory system in a manner that facilitates the search for appropriate food sources. In this video article, we describe an automated assay to measure the effect of hunger or satiety on olfactory dependent food search behavior in the adult fruit fly Drosophila melanogaster. In a light-tight box illuminated by red light that is invisible to fruit flies, a camera linked to custom data acquisition software monitors the position of six flies simultaneously. Each fly is confined to walk in individual arenas containing a food odor at the center. The testing arenas rest on a porous floor that functions to prevent odor accumulation. Latency to locate the odor source, a metric that reflects olfactory sensitivity under different physiological states, is determined by software analysis. Here, we discuss the critical mechanics of running this behavioral paradigm and cover specific issues regarding fly loading, odor contamination, assay temperature, data quality, and statistical analysis.

A Single-fly Assay for Foraging Behavior in Drosophila

In this video article, we describe an automated assay to measure the effect of hunger or satiety on olfactory dependent food search behavior in the adult fruit fly Drosophila melanogaster.

单苍蝇检测方法的觅食行为的<em&gt;果蝇</em

For many animals, hunger promotes changes in the olfactory system in a manner that facilitates the search for appropriate food sources. In this video ...

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 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. ...

A Simple Way to Measure Alterations in Reward-seeking Behavior Using Drosophila melanogaster

We describe a protocol for measuring ethanol self-administration in fruit flies (Drosophila melanogaster) as a proxy for changes in reward states. We demonstrate a simple way to tap into the fly reward system, modify experiences related to natural reward, and use voluntary ethanol consumption as a measure for changes in reward states. The approach serves as a relevant tool to study the neurons and genes that play a role in experience-mediated changes of internal state. The protocol is composed of two discrete parts: exposing the flies to rewarding and nonrewarding experiences, and assaying voluntary ethanol consumption as a measure of the motivation to obtain a drug reward. The two parts can be used independently to induce the modulation of experience as an initial step for further downstream assays or as an independent two-choice feeding assay, respectively. The protocol does not require a complicated setup and can therefore be applied in any laboratory with basic fly culture tools.

A Simple Way to Measure Alterations in Reward-seeking Behavior Using Drosophila melanogaster

We describe a protocol for inducing rewarding and nonrewarding experiences in fruit flies (Drosophila melanogaster) using voluntary ethanol consumption as a measure for changes in reward states.

一个简单的方法来衡量在改建悬赏寻求行为使用<em&gt;果蝇</em

We describe a protocol for measuring ethanol self-administration in fruit flies (Drosophila melanogaster) as a proxy for changes in reward states. We ...