Name: a quantitative fitness analysis workflow
Uploaded: 2012-08-13T12:00:00
Duration: 11 min 39 s
Description: Watch this Scientific Journal Video about A Quantitative Fitness Analysis Workflow at JoVE.com

我们非常感谢我们的实验室和老龄​​化，支持和有益的讨论营养（CISBAN）集成系统生物学中心的所有成员。这项研究是由生物技术和生物科学研究理事会（BBSRC）（BB/C008200/1）和威康信托基金会（075294，093088）。

手动，QFA协议（ 酵母菌株 ） 1。培养酵母菌株<ol><li> 96个独立的酵母菌株在200μL丰富的液体介质，在96培养皿培养。株生长饱和控制孵化温度。 </li><li>一个96针，1/8“直径手册副本柏列达（西格玛的R-2508）第一副本柏列达在100％的乙醇浸泡，燃烧，然后离开降温消毒。 </li><li> 200μl无菌水的排列在96孔培养板。饱和的文化振荡（Eppendorf公司MixMate，30秒，750转），浸入饱和株三次消毒的针工具板含有水一次，然后稀释。 </li><li>针工具重新消毒为1.2。 </li><li>用于灭菌的针工具发现上出售的琼脂平板稀释文化浸入板中含有稀释的文化三倍列印转移到一个长方形的固体琼脂平板上的针工具。 </li><li>长方形的固体琼脂平板培养在适当的温度前手动使用标准普尔机器人spImager成像。可替代的图像采集方法也可以使用，如富士LAS4000，或更便宜的数码单反相机，如果已采取审慎措施确保即使照明和成像相机相对一致的车牌定位。 </li><li>该方法是适应平行的文化，如48，可装上一轮培养皿，如果已采取审慎措施确保在每张照片成像相机相同的角度相对较小的数字。 </li></ol>全自动QFA协议（ 酵母菌株 ） 2。培养酵母菌株<ol><li>启动一个独立的酵母菌株固体琼脂上生长的矩形阵列。在这个例子中，出发菌株过温度（YDC）由合成基因阵列（SGA）的酵母删除收集敏感的查询突变。最后SGA的板块是在1536年的格式。这是16行24列代表四个殖民地/文化，384个独立的酵母菌株的复制。板布局见图1。 </li><li>使用了96针，针直径1毫米无菌pintool成4个96孔培养板含有选择性培养基200μL（ 图1）S＆P的机器人公司BM3-SC机器人，机器人被转移了1536年的384株。 pintool洁净和无菌实现顺序在无菌水清洗两次（一次一个旋转的刷子，清除杂物），70％的乙醇（超声）和最后100％的乙醇。 </li><li>文化发展到饱和（3天在20°C在这个例子中，参见图1）。 </li></ol> 3。发现酵母培养<ol><li>使用1贝克曼Biomek FX，饱和文化重新悬浮涡旋上的Variomag Teleshake（1000RPM逆时针20秒）和稀释成200μL无菌水寄希望于用无菌的96针机器人针工具（V＆P科学磁性安装pintool，2毫米针直径）约1:70。针工具的清洁和无菌，无菌水冲洗，在70％乙醇洗涤（用刷子清除杂物），最后经干燥70％的乙醇浸泡。 </li><li>察觉到384格式使用相同的机器人针工具（ 见图1）清洗和消毒后的固体琼脂板稀释的文化。 </li><li>板固定后，被转移到一个Cytomat温度控制，加湿的孵化器与自动传送带和出入舱口。 </li></ol> 4。图像捕捉<ol><li>标准普尔机器人自动化成像反复删除板块从Cytomat孵化器，消除了板盖，根据一项附上他们正是D，均匀照射下佳能EOS反叛钛135数码单反的空间，在5184 x 3456像素分辨率图像捕获，取代了板盖，并返回他们的孵化器传送带。紧随最初转移到孵化时间点零增长的测量（背景）允许一个图像被捕获。机器人处理和摄影每盘需要2分钟。 </li><li>随着一辆满载的传送带，达到最大的板图像采集频率是一张照片，每六个小时。板培养6天（直到菌落生长饱和。 图1显示了三种典型的图像从一个时间过程，在20°C </li><li>用于跟踪目的，板被命名为根据孵化器的名称，温度，独特的序批数和在孵化器的位置。图片名称是串联板的名称和时间戳和自动图像采集后兴建（如K000011_030_010_2011-09-22_09-47-54.jpg，文件类型FT1， 表1）。 </li></ol> 5。实验元数据捕获本节中描述的元数据文件是制表符分隔的文本文件手动产生（例如，使用电子表格软件）。每次实验，实验的描述文件（FT2， 表1）是独一无二的，但图书馆描述氨酸（FT3， 表1）可以重新广泛使用一次构建。 <ol><li>实验中介绍了实验的描述文件，包含条码列（或自动生成的板块名称）（FT2， 表1），实验开始时间戳，板治疗，固体琼脂培养基，屏幕上的名字，图书馆，车牌号码（内容与图书馆多板）和重复象限数量从1536格式缩减到384格式（ 见图1）。 </li><li>酵母菌株库库描述文件（FT3， <stronG&gt;表1），说明生长在每个图书馆在每个板的文化位置的基因型。它包含列：库的名称，框，车牌号码，板排板列和列可选票据。 </li><li>可以提供一个可选的标准基因名称文件（FT4水平， 表1）描述每个系统的ORF Y-号码识别正在筛选菌株（如YDR217C）相关标准的基因名称（如RAD9）。此文件包含两列：ORF的基因名称。 </li></ol> 6。数据分析 QFA计算的工作流程需要访问一个相当强大的多核计算机工作站（如至强四核2.67 GHz处理器和12GB内存的戴尔Precision T3500）上安装的Colonyzer图像分析软件工具，3,4和QFA R包7 ，这两者都是网上记录，都可以免费上运行的操作系统范围。 <ol><li>运行捕获板作为输入图像的每一个Colonyzer，为每个捕获的图像中产生一个Colonyzer输出文件（FT5 表1）。 colonyzer输出文件指定的养殖密度估计，文化领域，为每个384位置上的成像板的形状和颜色。输出文件名 ​​会自动复制源图像文件名 ​​（如板照片K000011_030_010_2011-09-22_09-47-54.jpg（FT1加热， 表1）对应的Colonyzer输出文件K000011_030_010_2011-09-22_09-47-54.dat（ FT5， 表1））。 </li><li>使用QFA R包，加载实验的元数据（FT2， 表1）和Colonyzer输出文件（FT5 表1）。这些数据合并到R的数据帧（QFA原始数据的文本文件“（FT6， 表1）可作为出口）作进一步的分析。 </li><li> QFA R包中包含的功能，以收集每一种文化细胞密度timecourses的，适合一概而论劳的GISTIC人口的意见和绘图模型（见图2和图3的例子）。拟合参数值被写入QFA物流参数文件（FT7 表1）。见QFA R为进一步的细节包的文档。 </li><li> QFA R包还包含质量控制功能：边缘殖民地板边缘和困难，由于提供更多的营养物质被丢弃在附近的钢板墙，文化未能SGA和基因型显示屏幕的特定标记基因的连锁与图像分析从分析中被剥离。 </li><li>来自Logistic人口模型参数为每个文化几个定量的健身​​措施。其中包括最大的人口倍增率（MDR）和部门的数量从接种到饱和度（MDP）。为每个复制的文化集（例如独特的基因型），并为每个健身的定义，健身估计数汇总统计，排版uted：平均数和中位数的健身，健美的标准偏差和数量的重复观测。汇总统计数据输出QFA健身概要文件（FT8， 表1），作进一步的分析，如计算遗传相互作用分数（FT9 表1）。 </li></ol> 7。代表结果 图2显示了一个典型的增长384 QFA增长在20°C固体琼脂由Colonyzer量化，随着细胞密度的增加大约2天之后首次成为检测文化的曲线。这种延迟可能是文化的滞后期后接种到固体培养基和细胞密度较低的检测限制的综合效应。 图3显示了从一个单一的板捕获的308类似的增长曲线图4显示了两个全基因组的比较QFA屏幕推断遗传互动优势（从1改编）。 QFA R包7还包括功能产生图3和输出研究基因型和遗传相互作用的强度（GIS）的估计排名名单，一个Q值（错误发现率（FDR）的校正p值）观测到的地理信息系统的意义。 <img alt="图1" src="/files/ftp_upload/4018/4018fig1.jpg" /> 图1。在384点的格式为机器人的酵母菌株接种计划。此过程始于1536独立文化（左）每盘。在这个典型的例子，殖民地位1,1; 1,2; 2,1和2,2（红色）四个重复相同的基因型HIS3 ::黄色KANMX文化，生长板边缘。 ，有一个增长的优势，由于缺乏竞争，因此不QFA检查。这些复制（如1,1）在96孔板接种到液体培养基<html>使用96针的工具，接种1536菌落每次96。接种，以接种四个不同的“象限”（显示为红色，蓝色，绿色和紫色）​​的384个基因的缺失，每一个复制到四个不同的96孔含生长介质板。文化增长饱和（如3天在20°C）后，用水稀释，然后从一个重复的四个象限察觉到了坚实的琼脂板（右）在SGA的原板相同的模式，在384格式（颜色表示）。这个过程可以重复测试其他的复制：1,2，2,1和2,2。例如时间推移右侧的图像被抓获接种后0.5年，2年和3.5天。调整补充图1 2。 <a href="http://www.jove.com/files/ftp_upload/4018/4018fig1large.jpg" target="_blank">点击这里查看大图</a> 。 018/4018fig2.jpg“/&gt; 图2。一个单一的机器人捕获的QFA生长曲线A）QFA增长20琼脂中含半乳糖的酵母菌株的生长曲线°C。图像被抓获机器人大约每2个小时。指数相在此温度下，观察到约1.5天，与养殖密度的增加，首次成为检测接种后约2天​​。广义Logistic模型是适合的观测数据（灰色曲线）。 QFA R包自动装配模型的参数是：K（承载能力（非盟）），R（增长率（四-1）），G（接种密度（非盟）），V（增长对称）。 b）一个面板，日志规模与 ​​细胞密度的绘制。 <a href="http://www.jove.com/files/ftp_upload/4018/4018fig2large.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图3" src="/files/ftp_upload/4018/4018fig3.jpg" /> 图3。自动基因<html>额定生长曲线捕获从一个单一的384格式板平行。每个面板显示细胞密度估计（红叉）和独立的文化标记基因名称或框ŸQFA过程中生长模型拟合（黑色曲线）。这个例子板​​成像和机器人在自动孵化成长，在20°C实验的元数据将自动列入图中的标题：名盘，板治疗，琼脂培养基和图书馆车牌号码。拟合模型的参数值也自动打印在每个面板（见图2）。边缘文化被剥夺QFA分析，留在这个小区的308文化（见QFA议定书5.4）。由于边缘文化不QFA分析，这些文化的地点通常是充满了中性的控制株（在这种情况下pGAL-HIS3）。 QFA R包的输出，这个数字的原始版本，是PDF格式，因此是无限可缩放和可检索的文本查询。:/ / www.jove.com/files/ftp_upload/4018/4018fig3.pdf“的目标=”_blank“&gt;点击这里查看大图。 <img alt="图4" src="/files/ftp_upload/4018/4018fig4.jpg" /> 图4。两个QFA屏幕比较适应度来推断基因的相互作用。此图显示了芽殖酵母结合中性ura3Δ突变或对温度敏感的cdc13-1突变，生长在半放任温度缺失（yfgΔ）的健身比较cdc13 1（27℃）。健身计算作为最大的速度提高一倍的产品和最大倍增潜力1。大多数缺失株生长良好，与的中性ura3Δ突变结合，如预期，并具有较高的健身，但结合cdc13-1的缺失，有广泛的适应度。淡蓝色的线交叉在日ê的的中性his3Δ突变的位置，实线是线性回归模型的遗传独立性（cdc13-1预计健身yfgΔ突变体健身的ura3ΔyfgΔ突变）和虚线是平等健身行。缺失色绿，显着提高健身cdc13-1株的缺陷。删除红色显着抑制相同的缺陷。任何突变cdc13-1yfgΔ实线的垂直距离显示板条件下cdc13-1和yfgΔ之间的遗传相互作用的强度。注cdc13-1最强的抑制一些先前发现的右上角附近的检查点基因，RAD17，DDC1和RAD24和核酸EXO1。基因的缺失降低健身包括附近YKU80（编码DNA修复和端粒封盖蛋白Yku80）<html>右下角。还注意到，一些团体共同发挥作用的基因，往往会被位于该地块上合作。强调在蓝色SPE1，SPE2和SPE3的三个例子集群：亚精胺合成的基因，RAD17，DDC1和RAD24：检查点滑动钳和检查站钳装载机，MRE11，RAD50和XRS2编码组件的MRX复杂，在DDR和EST1的参与EST3：基因参与端粒长度调节。改编自补充图1B 1，从这个情节产生的原始数据，可以从这里下载： <a href="http://research.ncl.ac.uk/colonyzer/AddinallQFA/" target="_blank">http://research.ncl.ac.uk/colonyzer/AddinallQFA/</a> 。 <a href="http://www.jove.com/files/ftp_upload/4018/4018fig4.pdf" target="_blank">点击这里查看大图</a> 。 “&gt; <tbody><tr><td> 文件编号 </td><td> 文件类型 </td><td> 手动构造 </td><td> 更新频率 </td><td> 条件 </td></tr><tr><td> FT1 </td><td>板照片</td><td>没有</td><td>每板及时间点</td><td>是</td></tr><tr><td> FT2 </td><td>实验说明</td><td>是</td><td>每个实验</td><td>是</td></tr><tr><td> FT3 </td><td>图书馆简介</td><td>是</td><td>每个库</td><td>是</td></tr><tr><td> FT4水平</td><td>标准基因名称</td><td>是</td><td>每个库</td><td>没有</td></tr><tr><td> FT5 </td><td> colonyzer输出继电器</td><td>没有</td><td>每盘时间点</td><td>是</td></tr><tr><td> FT6 </td><td> QFA原始数据</td><td>没有</td><td>每个实验</td><td> - </td></tr><tr><td> FT7 </td><tD&gt; QFA物流参数</td><td>没有</td><td>每个实验</td><td> - </td></tr><tr><td> FT8 </td><td> QFA健身摘要</td><td>没有</td><td>每个实验</td><td> - </td></tr><tr><td> FT9 </td><td> QFA遗传相互作用Hitlist </td><td>没有</td><td>每地理信息系统研究（2 expts。） </td><td> - </td></tr></tbody></table> 表1。电子QFA文件。列出的所有文件（除FT1）是制表符分隔的文本文件，可以使用任何文本编辑器或电子表格软件建造或阅读。关于构建QFA元数据文件和QFA输出的精确解释的进一步详细信息，请参阅的QFA R包文件7和Colonyzer软件文档3。 <img src="/files/ftp_upload/4018/4018table2.jpg" alt="表2" /> 表2。评估文化健身方法。总结的特点和要求ments的评估微生物培养健身方法。审查布隆贝格8包含其中一些更详细的比较。 <a href="http://www.jove.com/files/ftp_upload/4018/4018table2large.jpg" target="_blank">点击这里查看大图</a> 。

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没有利益冲突的声明。

QFA是在许多感官的直接后裔三立台规模的微生物技术：文化系列稀释现场测试9，生长曲线的测定充气液体培养和副本电镀13。这三种方法进行了总结和与QFA和其他高通量技术在表2比较。而稀释系列现场测试定义为应变能力，形成一系列种植范围从接种稀释的文化殖民地的健身，QFA措施，由一个单一的文化反复观察应变健身构建一个增长曲线。量化健身从单一的文化，让更多株进行检查，同时在相同条件下。文化复制阵列允许重复的应变集合，最有效的测试时，测试在不同的环境或遗传背景的文化健身差异。 QFA协议介绍这里使用昂贵的机器设备，复制，接种，孵育和图像琼脂平板上，适当的观察数以千计的独立文化（机器人QFA， 表2）的增长。然而，由于QFA是既定的，传统的实验室技术为基础，它也可以进行更便宜，取代手工步骤（手动QFA， 表2）机器人援助。手动QFA涉及复制和接种到琼脂平板上培养使用手册针板和摄影的孵化器的工具和手动传输。可应用于相同的计算分析工作流程，无论从实验设计产生的生长曲线。 QFA健身的估计似乎是比较精确。在图4中，突出四个功能相关的基因缺失，例如集群的平均适应度。每个功能相关的基因类成员的接近两independ耳鼻喉科遗传背景（ura3Δ和cdc13-1）表示QFA健身估计的可重复性。例如，只有3个基因缺失（走出了一条可能的4300）分开保守的MRX复杂的三名成员。 QFA为测试微生物菌种的生长特性，高吞吐量的替代品，包括SGA的5,6，竞争屏幕11,12条码库和屏幕捕捉光密度动力学分光板读者10总结在表2和更全面的描述别处8 。 QFA和SGA板，文化固体琼脂表面（琼脂为基础的方法， 表2）成长由机器人可以快速，轻松地处理。固体琼脂表面培养良好的透气性，整个生长和细胞可以生长在固定的文化，让交际的微生物生长在一个社区14。原封不动，微生物群落ffect自己的微环境，如乙醇分泌毒素，并可能在细胞之间的信号。然而，连续的混合液体培养，要达到足够的通风，人为破坏微生物群落和它们的微环境，这可能会影响他们的成长模式。交叉污染是在固体琼脂方法的关注，因为有较少的机会进行不同文化之间的细胞的液体飞溅。如果外国空气传播，在固体琼脂检测微生物污染时，它往往可以通过目测固体琼脂平板进行检测，并占或删除。 QFA吞吐量明显比两种方式并行的液体方法。首先，QFA（SGA）的板，接种培养挤在一起更密集，给每盘更独立的文化。在QFA通常有308文化，不计非实验性的边缘文化（ 图1）COM相比，每盘96或100文化与平行的液体培养。其次，QFA实验还可以扩展到更大的板材数量。 QFA在一个单一的实验分析板的数量，而只由孵化器或温暖的房间里，允许的最小图像采集频率和达到的最大捕获频率的可用空间的限制，在液体中的生长实验板的数量是强烈有限酶标仪（通常是一个或两个板块），或连接到酶标仪（通常为25-50板）的堆的容量。最近，我们进行完全自动化的QFA上123板，每个实验308实验的文化，同时给予37884文化。我们估计，在液体中越来越多的独立文化的最大实现数是96（文化/板）×50（板/堆叠器）= 4800，这是QFA吞吐量比我们少十倍左右。液体培养屏幕的另一种方法是利用许多自动化GROWTH设备并行（ 表从审查布隆贝格8 1），每有一个或两个板块的能力。在每个设备的温度控制是独立的，这样的条件是不相同的，但假设它们，这个工作流程将需要至少190个此类设备QFA吞吐量（假设200％液体培养设备）相匹配。 总之，QFA是一个高质量的工作流程，可以有效地聚集在数量增长的表型集中两个小规模试验和高通量筛选。它是足够灵活，有效地应用于机器人设备的要求不一。 QFA工作流程的计算组件的基础上的自由，开放的源代码。

<table border="1"><tbody><tr><td> 试剂/设备名称 </td><td> 公司 </td><td> 目录编号 </td><td> 评论 </td></tr><tr><td>副本柏列达</td><td>西格玛</td><td>的R-2508 </td><td> 96 1/8“直径针针手工pintool </td></tr><tr><td>混合伴侣</td><td> Eppendorf公司</td><td> 5353 000.014 </td><td></td></tr><tr><td> biomek外汇</td><td>贝克曼</td><td> A31842 </td><td></td></tr><tr><td> teleshake </td><td> Thermo Scientific的</td><td> 50095890 </td><td>安装在Biomek外汇</td></tr><tr><td> BM3-SC </td><td>标准普尔机器人公司</td><td> BM3-SC </td><td> 192货架旋转传送带</td></tr><tr><td> spImager </td><td>标准普尔机器人公司</td><td> spImager </td><td>高分辨率手册成像</td></tr><tr><td> spImager与Cytom在</td><td>标准普尔机器人公司</td><td>习俗</td><td>温度控制自动高分辨率成像</td></tr><tr><td> 6001 cytomat与热交换器</td><td> Thermo Scientific的</td><td> 51022222 </td><td>附以spImager </td></tr><tr><td> ECOLINE RE207 </td><td>劳达</td><td> RE207 </td><td>附以Cytomat </td></tr><tr><td> spImager与传送带</td><td>标准普尔机器人公司</td><td>习俗</td><td>自动高分辨率成像</td></tr><tr><td>机器人针FP12pins工具夹具</td><td> V和P级科学</td><td> AFIX96FP12 </td><td> N / A </td></tr><tr><td> 96×FP12引脚</td><td> V和P级科学</td><td> FP12 </td><td> 50.4毫米长，17毫米露出针脚长度</td></tr><tr><td>停靠站为脚工具</td><td> V和P级科学</td><td> VP425 </td><td>坞站基地中删除允许引脚风扇干燥</td></tr><tr><td>针清洁刷</td><td> V和P级科学</td><td> VP425 </td><td> N / A </td></tr><tr><td>副本柏列达</td><td>西格玛</td><td>的R-2508 </td><td>手动脚工具</td></tr><tr><td> NUNC OmniTray盖</td><td> NUNC </td><td> 734-0490 </td><td> N / A </td></tr><tr><td> 96孔无菌的聚苯板</td><td>格雷纳BioOne </td><td> 655161 </td><td> N / A </td></tr><tr><td> 96孔无菌聚苯乙烯盖</td><td>格雷纳BioOne </td><td> 656171 </td><td> N / A </td></tr></tbody></table> 表3。特定的试剂和设备。

a quantitative fitness analysis workflow

定量健身分析（QFA）是为适应度比较在1,2,3,4平行生长的微生物培养的实验和计算的工作流程。 QFA可以应用于单一文化的集中的意见，而且是最有用的全基因组的遗传相互作用或药物屏幕调查到数以千计的独立文化。中央实验方法是独立的，稀的液体微生物固体琼脂平板上培养和定期拍下文化的接种。从每个时间点的照片进行了分析，生产定量细胞密度估计，这是用来兴建的生长曲线，从而得到定量的健身​​措施。文化适应度可以比较量化和排序遗传相互作用的优势或药物的敏感性。任何治疗的健身文化的影响补充到基板琼脂（如小分子物质，抗生素或营养）或适用于板的外部LY（如紫外线照射，温度），可量化的QFA。 QFA工作流程产生类似于光度法测量平行的液体培养在96孔或200井板读者获得的增长率估计。重要的是，QFA与这些方法相比有显着更高的吞吐量。 QFA文化上生长了坚实的琼脂表面，因此在增长，而不需要进行搅拌或摇晃充气。 QFA吞吐量不高，一些合成基因阵列（SGA）的筛选方法5,6。然而，由于严重之前被接种到琼脂稀释QFA文化，QFA可以捕捉更完整的生长曲线，包括指数和饱和阶段3。例如，生长曲线观察允许直接与高精度培养倍增时间估计，作为讨论以前1。 在这里，我们提出了具体QFA协议适用于成千上万的S.酵母是由机器人自动处理文化在孕育，孵化和成像。这些自动化的任何步骤可以由具有同等作用，手动程序取代，吞吐量减少，我们也提出一个较低的吞吐量手册协议。 QFA相同的软件工具可以应用在任何工作流程中捕获的图像。 我们有丰富的经验，申请QFA芽殖酵母培养学酵母 ，但我们预计，，QFA将证明裂殖酵母为研究文化同样有用S。酵母和细菌培养。

Watch this Scientific Journal Video about A Quantitative Fitness Analysis Workflow at JoVE.com

A Quantitative Fitness Analysis Workflow

健身定量分析（QFA）是一系列估计微生物培养适应度的实验和计算方法的互补。 QFA估计的基因突变，药物或其他适用于微生物的生长治疗的效果。可以设计实验缩放从单一文化的集中分析数以千计的并行文化。

定量健身分析工作流程

Quantitative Fitness Analysis (QFA) is an experimental and computational workflow for comparing fitnesses of microbial cultures grown in parallel1,2,3,4. ...

Research

JoVE Journal

Biology

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

一个神经元和星形胶质细胞共培养检测神经毒性的高含量分析

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

科研

生物学

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

This protocol describes the growth and stimulation, with the fatty acid oleate, of isotopically heavy and light S. cerevisiae cells. Cells are ground using a cryolysis procedure in a ball mill grinder and the resulting grindate brought into solution by urea solubilization. This procedure allows for the lysis of the cells in a metabolically inactive state, preserving phosphorylation and preventing reorientation of the phosphoproteome during cell lysis.  Following reduction, alkylation, trypsin digestion of the proteins, the samples are desalted on C18 columns and the sample complexity reduced by fractionation using hydrophilic interaction chromatography (HILIC). HILIC columns preferentially retain hydrophilic molecules which is well suited for phosphoproteomics.  Phosphorylated peptides tend to elute later in the chromatographic profile than the non phosphorylated counterparts. After fractionation, phosphopeptides are enriched using immobilized metal chromatography, which relies on charge-based affinities for phosphopeptide enrichment. At the end of this procedure the samples are ready to be quantitatively analyzed by mass spectrometry.

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

Description of a quantitative phosphorylation procedure using cryolysis, urea solubilziation, HILIC fractionation and IMAC enrichment of phosphorylated peptides.

脂肪酸定量磷酸化刺激酿酒酵母</em

This protocol describes the growth and stimulation, with the fatty acid oleate, of isotopically heavy and light S. cerevisiae cells. Cells are ground ...

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Embryonic epithelial cells serve as an ideal model to study morphogenesis where multi-cellular tissues undergo changes in their geometry, such as changes in cell surface area and cell height, and where cells undergo mitosis and migrate. Furthermore, epithelial cells can also regulate morphogenetic movements in adjacent tissues1. A traditional method to study epithelial cells and tissues involve chemical fixation and histological methods to determine cell morphology or localization of particular proteins of interest. These approaches continue to be useful and provide "snapshots" of cell shapes and tissue architecture, however, much remains to be understood about how cells acquire specific shapes, how various proteins move or localize to specific positions, and what paths cells follow toward their final differentiated fate. High resolution live imaging complements traditional methods and also allows more direct investigation into the dynamic cellular processes involved in the formation, maintenance, and morphogenesis of multicellular epithelial sheets. Here we demonstrate experimental methods from the isolation of animal cap tissues from Xenopus laevis embryos to confocal imaging of epithelial cells and simple measurement approaches that together can augment molecular and cellular studies of epithelial morphogenesis.

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Xenopus embryonic epithelia are an ideal model system to study cell behaviors such as polarity development and shape change during epithelial morphogenesis. Traditional histology of fixed samples is increasingly being complemented by live-cell confocal imaging. Here we demonstrate methods to isolate frog tissues and visualize live epithelial cells and their cytoskeleton using live-cell confocal microscopy.

活细胞成像和胚胎上皮细胞的定量分析非洲爪蟾</em

Embryonic epithelial cells serve as an ideal model to study morphogenesis where multi-cellular tissues undergo changes in their geometry, such as changes ...

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using fluorochromes like Green Fluorescent Protein (GFP) directly attached to the protein of interest has become increasingly popular 1. Using GFP and similar fluorochromes the subcellular localisations and movements of proteins can be detected in a fluorescent microscope. Moreover, also the subnuclear localisation of a certain region of a chromosome can be studied using this technique. GFP is fused to the Lac Repressor protein (LacR) and ectopically expressed in the cell where tandem repeats of the lacO sequence has been inserted into the region of interest on the chromosome2. The LacR-GFP will bind to the lacO repeats and that area of the genome will be visible as a green dot in the fluorescence microscope. Yeast is especially suited for this type of manipulation since homologous recombination is very efficient and thereby enables targeted integration of the lacO repeats and engineered fusion proteins with GFP 3. Here we describe a quantitative method for live cell analysis of fission yeast. Additional protocols for live cell analysis of fission yeast can be found, for example on how to make a movie of the meiotic chromosomal behaviour 4. In this particular experiment we focus on subnuclear organisation and how it is affected during gene induction. We have labelled a gene cluster, named Chr1, by the introduction of lacO binding sites in the vicinity of the genes. The gene cluster is enriched for genes that are induced early during nitrogen starvation of fission yeast 5. In the strain the nuclear membrane (NM) is labelled by the attachment of mCherry to the NM protein Cut11 giving rise to a red fluorescent signal. The Spindle Pole body (SPB) compound Sid4 is fused to Red Fluorescent Protein (Sid4-mRFP) 6. In vegetatively growing yeast cells the centromeres are always attached to the SPB that is embedded in the NM 7. The SPB is identified as a large round structure in the NM. By imaging before and 20 minutes after depletion of the nitrogen source we can determine the distance between the gene cluster (GFP) and the NM/SPB. The mean or median distances before and after nitrogen depletion are compared and we can thus quantify whether or not there is a shift in subcellular localisation of the gene cluster after nitrogen depletion.

The fission yeast, Schizosaccharomyces pombe, is a good model system to study basic cellular processes. Here we describe a method to perform quantitative live cell analysis of fission yeast. In this particular experiment we focus on organisation of the genome within the cell nucleus, but the method can also be used to study cytosolic factors.

裂殖酵母的活细胞定量荧光显微镜分析

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

随机使用时移视频显微镜细胞迁移的定量分析

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, traditional chemotherapeutic approaches have been largely unsuccessful. Hormone therapy is effective at early stage, but often fails with the eventual development of hormone-refractory tumors. We have been interested in developing therapeutics targeting specific metabolic deficiency of tumor cells. We recently showed that prostate tumor cells specifically lack an enzyme (argininosuccinate synthase, or ASS) involved in the synthesis of the amino acid arginine1. This condition causes the tumor cells to become dependent on exogenous arginine, and they undergo metabolic stress when free arginine is depleted by arginine deiminase (ADI)1,10. Indeed, we have shown that human prostate cancer cells CWR22Rv1 are effectively killed by ADI with caspase-independent apoptosis and aggressive autophagy (or macroautophagy)1,2,3. Autophagy is an evolutionarily-conserved process that allows cells to metabolize unwanted proteins by lysosomal breakdown during nutritional starvation4,5. Although the essential components of this pathway are well-characterized6,7,8,9, many aspects of the molecular mechanism are still unclear - in particular, what is the role of autophagy in the death-response of prostate cancer cells after ADI treatment? In order to address this question, we required an experimental method to measure the level and extent of autophagic response in cells - and since there are no known molecular markers that can accurately track this process, we chose to develop an imaging-based approach, using quantitative 3D fluorescence microscopy11,12.
Using CWR22Rv1 cells specifically-labeled with fluorescent probes for autophagosomes and lysosomes, we show that 3D image stacks acquired with either widefield deconvolution microscopy (and later, with super-resolution, structured-illumination microscopy) can clearly capture the early stages of autophagy induction. With commercially available digital image analysis applications, we can readily obtain statistical information about autophagosome and lysosome number, size, distribution, and degree of colocalization from any imaged cell. This information allows us to precisely track the progress of autophagy in living cells and enables our continued investigation into the role of autophagy in cancer chemotherapy.

Autophagy is a ubiquitous process that enables cells to degrade and recycle proteins and organelles. We apply advanced fluorescence microscopy to visualize and quantify the small, but essential, physical changes associated with the induction of autophagy, including the formation and distribution of autophagosomes and lysosomes, and their fusion into autolysosomes.

采用先进的3D荧光显微镜定量分析自噬

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, ...

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Biochemical assays with recombinant human MHC II molecules can provide rapid, quantitative insights into immunogenic epitope identification, deletion, or design1,2. Here, a peptide-MHC II binding assay is scaled to 384-well format. The scaled down protocol reduces reagent costs by 75% and is higher throughput than previously described 96-well protocols1,3-5. Specifically, the experimental design permits robust and reproducible analysis of up to 15 peptides against one MHC II allele per 384-well ELISA plate. Using a single liquid handling robot, this method allows one researcher to analyze approximately ninety test peptides in triplicate over a range of eight concentrations and four MHC II allele types in less than 48 hr. Others working in the fields of protein deimmunization or vaccine design and development may find the protocol to be useful in facilitating their own work. In particular, the step-by-step instructions and the visual format of JoVE should allow other users to quickly and easily establish this methodology in their own labs.

Biochemical assays with recombinant human MHC II molecules can provide rapid, quantitative insights into immunogenic epitope identification, deletion, or design. &#160;Here, a peptide-MHC II binding assay scaled to 384-well plates is described. This cost effective format should prove useful in the fields of protein deimmunization and vaccine design and development.

高通量MHC II类分子结合分析抗原表位肽的定量分析

Biochemical assays with recombinant human MHC II molecules can provide rapid, quantitative insights into immunogenic epitope identification, deletion, or ...

A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis

Alopecia is a common form of hair loss which can occur in many different conditions, including male-pattern hair loss, polycystic ovarian syndrome, and alopecia areata. Alopecia can also occur as a side effect of chemotherapy in cancer patients. In this study, our goal was to develop a consistent and reliable method to quantify hair loss in mice, which will allow investigators to accurately assess and compare new therapeutic approaches for these various forms of alopecia. The method utilizes a standard gel imager to obtain and process images of mice, measuring the light absorption, which occurs in rough proportion to the amount of black (or gray) hair on the mouse. Data that has been quantified in this fashion can then be analyzed using standard statistical techniques (i.e., ANOVA, T-test). This methodology was tested in mouse models of chemotherapy-induced alopecia, alopecia areata and alopecia from waxing. In this report, the detailed protocol is presented for performing these measurements, including validation data from C57BL/6 and C3H/HeJ strains of mice. This new technique offers a number of advantages, including relative simplicity of application, reliance on equipment which is readily available in most research laboratories, and applying an objective, quantitative assessment which is more robust than subjective evaluations. Improvements in quantification of hair growth in mice will improve study of alopecia models and facilitate evaluation of promising new therapies in preclinical studies.

Alopecia is a common form of hair loss which can occur in many different conditions, including as a side-effect of chemotherapy. We have developed a method to quantify hair loss in mice, utilizing a standard gel imager to perform a grayscale analysis, to facilitate study of promising new alopecia therapies.

新技术脱发的定量分析小鼠使用灰度分析

Alopecia is a common form of hair loss which can occur in many different conditions, including male-pattern hair loss, polycystic ovarian syndrome, and ...

Complete Workflow for Analysis of Histone Post-translational Modifications Using Bottom-up Mass Spectrometry: From Histone Extraction to Data Analysis

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone function is mediated by extensive post-translational modification by a myriad of nuclear proteins. These modifications are critical for nuclear integrity as they regulate chromatin structure and recruit enzymes involved in gene regulation, DNA repair and chromosome condensation. Even though a large part of the scientific community adopts antibody-based techniques to characterize histone PTM abundance, these approaches are low throughput and biased against hypermodified proteins, as the epitope might be obstructed by nearby modifications. This protocol describes the use of nano liquid chromatography (nLC) and mass spectrometry (MS) for accurate quantification of histone modifications. This method is designed to characterize a large variety of histone PTMs and the relative abundance of several histone variants within single analyses. In this protocol, histones are derivatized with propionic anhydride followed by digestion with trypsin to generate peptides of 5 - 20 aa in length. After digestion, the newly exposed N-termini of the histone peptides are derivatized to improve chromatographic retention during nLC-MS. This method allows for the relative quantification of histone PTMs spanning four orders of magnitude.

This protocol outlines a fully integrated workflow for characterizing histone post-translational modifications using mass spectrometry (MS). The workflow includes histone purification from cell cultures or tissues, histone derivatization and digestion, MS analysis using nano-flow liquid chromatography and instructions for data analysis. The protocol is designed for completion within 2 - 3 days.

完整的工作流程为组蛋白翻译后修饰的分析采用自下而上质谱法：从组蛋白提取数据分析

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone ...

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

The proteomic analysis of the human brain tissue over the last decade has greatly enhanced our understanding of the brain. However, brain related disorders continue to be a major contributor of deaths around the world, necessitating the need for even greater understanding of their pathobiology. Traditional antibody-based techniques like western blotting or immunohistochemistry suffer from being low-throughput besides being labor-intensive and qualitative or semi-quantitative. Even conventional mass spectrometry-based shotgun approaches fail to provide conclusive evidence to support a certain hypothesis. Targeted proteomics approaches are largely hypothesis driven and differ from the conventional shotgun proteomics approaches that have been long in use. Multiple reaction monitoring is one such targeted approach that requires the use of a special mass spectrometer called the tandem quadrupole mass spectrometer or triple quadrupole mass spectrometer. In the current study, we have systematically highlighted the major steps involved in performing a successful tandem quadrupole mass spectrometry-based proteomics workflow using human brain tissue with an aim to introduce this workflow to a broader research community.

The protocol aims to introduce the use of a triple quadrupole mass spectrometer for Multiple Reaction Monitoring (MRM) of proteins from clinical samples. We have provided a systematic workflow starting from sample preparation to data analysis for clinical samples with all the necessary precautions to be taken.