作者通过授予U54 RR022220和P50 GM076547向美国国家卫生研究院的JDA承认对此项工作的支持。 FDM是加拿大卫生研究所的博士后研究员。我们还感谢卢森堡系统生物医学中心和卢森堡大学的支持。

琼脂糖凝胶库的制备<ol><li>称量2 g高纯度琼脂糖。 </li><li>将琼脂糖加入500 mL瓶中，并记录其合并质量。 </li><li>用150克超纯水计算瓶子的目标质量和2克琼脂糖，然后加入150克超纯水至该目标物质的0.1克内。 </li><li>注意瓶子的质量加上琼脂糖和水。 </li><li>将瓶子放入微波炉中，确保将顶盖上的松散盖子装入瓶子，以尽量减少水分蒸发，同时加热琼脂糖。 </li><li>微波瓶子在15 - 20秒之间爆发，然后短暂地旋转瓶子来混合琼脂糖和水。重复此过程直到溶液沸腾并且混合物是均匀的。 小心:注意避免烫伤皮肤，避免蒸汽从瓶中逸出。此外，瓶子会变得很热，需要适当的保护，如高压灭菌手套，以避免受伤。</li><li>在熔融的琼脂糖均匀后，再次称重瓶子，并将超纯水加入原始质量的0.1克内。这将取代由于蒸发而损失的任何水分。 </li><li>在熔融的琼脂糖凝固之前，旋转以在加入的水中混合以确保均匀性。 </li><li>将15.2g琼脂糖等分成9-50mL塑料管。 </li><li>冷却管直到需要。 </li></ol>准备ODELAY琼脂糖介质<ol><li>加热400毫升去离子水，在一个盖烧杯中煮沸，在电热板上用一个磁力搅拌棒轻轻搅拌。 </li><li>在步骤1.10的50mL锥形管中加入2mL 10X培养基（ 例如酵母提取物胨（YEP）或Complete Supplement Mixture（CSM））至15.2g琼脂糖等分试样。 注意:CSM介质倾向于粘贴玻璃片。如果使用CSM培养基配方，在无菌水中加入5μL50％wt聚乙二醇（PEG）至培养基制剂。 PEG防止agar在脱模期间粘附到玻片上，并且不抑制酵母生长。 </li><li>如果需要，添加额外的100X营养补充剂，并使用水将总添加量从该步骤提升到1 mL。 </li><li>在将50mL锥形管置于步骤2.1的沸水中之前，称量琼脂糖等分试样加入培养基和补充剂。 </li><li> 16分钟后，取出50mL管，并用涡旋匀浆混合物。将盖子紧紧地紧固在50mL锥形管上。 注意:烧杯上的盖子有助于均匀加热整个管，否则会形成固体琼脂糖膜，也可能不熔化。此外，在此期间，组装琼脂糖模具是方便的（ 图1 ）。 </li><li>使用涡流使混合物均质化。 </li><li>煮沸另外2分钟，以确保所有琼脂混合和融化。 </li><li>称重管，并用超纯无菌水代替任何损失的物质。 </li><li>加入2 mL 10X碳酸ce试剂（ 例如 ，20％w / v葡萄糖）并涡旋以获得琼脂糖培养基溶液。 注意:玻璃滑块的分离:组装模具时，必须注意确保长的垫片以正确的方向放置在模具中。这是因为当激光切割丙烯酸时，它倾向于作为锥体切割，离开具有稍微倾斜的侧面的部分而不是恰好90°的侧面。然后当模具放置在台面上以从琼脂中释放玻璃时，间隔物的边缘应与琼脂成锐角。当模具间隔件的外边缘围绕下边缘枢转时，锐角有助于压缩琼脂的边缘远离上部玻璃板（ 见图1 ）。结果是琼脂与顶部玻璃片的分离更为一致。 注意:不要使用应用于玻璃的脱模剂，如油，硅喷雾剂甚至商业窗户处理，因为它们会污染s<html>琼脂的表面，可能抑制生长。这些方法采取一些做法是一致的。 </li><li>用70％乙醇清洗x 1 mm厚的玻璃载玻片中的4个2×2，并用强制空气干燥。 </li><li>用70％乙醇清洁丙烯酸模具，干燥并组装， 如图1所示。如图所示，拿起三个底部的零件，并组装它们，使两个相同的零件夹在第三个零件上（ 图1B ）。使用两个小夹子夹紧每侧的基片（ 图1C ）。将立柱放入模具中，确保激光切口正确定位（ 图1E ）。 </li><li>将清洁干燥的玻璃滑块放在模具上，并将其固定在另一侧。用较大的夹子夹紧组件（ 图1D ）。用较大的活页夹夹住两张幻灯片（lass ="xfig"&gt;图1D）。确保上粘结夹与玻璃滑块重叠与丙烯酸接触。 </li><li>添加剩余的剪贴簿夹。再次，确保夹具接触与丙烯酸重叠的滑块（ 图1D ）。 注意:在用熔融琼脂填充组装的模具之前，通过沿着模具内侧吸取约70μL的熔融琼脂介质来确保边缘被密封。这种琼脂将迅速凝固并防止任何泄漏。 </li><li>用熔融琼脂填充模具，确保避免在模具中捕获气泡。 注意:这可以通过沿着模具边缘慢慢吸取熔融琼脂来实现。填充后，允许模具在约23°C环境温度下冷却40分钟至1小时。如果允许冷却太久，琼脂可能在模具中断裂。 注意:模具分离:从浇注琼脂中正确移除模具对于确保均匀的固体至关重要琼脂垫用于酵母生长。不能确保在该步骤中模具的有效分离将导致由于固体琼脂垫中的缺陷而引起的生长差异。推荐几步练习。 </li><li>从底部夹子夹取下来。拆下由三个夹片组成的模具的底部。压缩幻灯片，然后取下夹子夹。拆卸夹子时，请勿碰到模具侧面。这会使媒体变形。 </li><li>将模具放在台面的边缘，以使具有蓝点的模具侧面朝上，并在左下角（ 图1E ）。将拇指放在丙烯酸酯的下方，将第一根手指放在模具的内边缘上。 </li><li>慢慢地，小心地用拇指向上推动模具，好像将模具隔片围绕其下边缘旋转（ 图1F ）。应用常数但缓慢增加的压力。用户将看到一个断裂，气泡出现在顶部玻璃覆盖模具间隔物的线上。 </li><li>看完初始断线后，继续用拇指向上推，施加恒压。此时琼脂应该从玻璃开始脱落（ 图1F ）。继续向上枢转模具。这样可以提起玻璃而不会滑动玻璃。琼脂从玻璃上剥离的线应该继续离开初始断裂线。 注意:此时，琼脂粘在玻璃的底部和顶部。这将偶尔会发生在最左边缘。只要变形区域不在发现酵母的地方，这应该是罚款。 </li><li>当玻璃完全自由时，抓住它并将其完全从模具中取出。然后使用类似的动作取出另一个模具，以便不移动琼脂来提升碎片。将幻灯片放在无菌尖端盒底部有一些无菌高纯度水。关闭盒子并储存在4°CO / N，以备第二天使用。如果储存更长时间，增长率将变得不一致。 </li></ol> ODELAY文化准备<ol><li>将菌株置于96孔板中进行O / N生长。 </li><li>第二天，将20μL的过夜培养物稀释到200μL的培养基中，在一个新的板中达到220μL的总体积。 </li><li>在平板阅读器中测量每种培养物的600nm（OD600）的光密度。使用读板机和液体处理机器人，遵循步骤3.3.1 - 3.3.6的自动稀释方案。将板中的培养物手动稀释至约0.1 OD600（可选）。 <ol><li>在读板器上，点击"创新"下的"实验"。选择ODELAYDilution.exp并运行实验。输入实验名称为ODELAY"日期""时间""实验名称"迭代。 </li><li>点击s纹身选项卡，然后单击Excel图标。将数据保存到拇指驱动器，并将其传输到液体处理机器人计算机。 </li><li>打开机器人的布局和方法编辑器。打开方法文件"ODELAYDilution_v1.med"。运行可执行文件"Convert_SynergyFiles.exe"。为目标OD600输入0.09。 </li><li>点击"Glu校正"和"Gal校正"为0.05。测量相同板材中的空白介质。点击"生成文件"。在方法编辑器中选择文件。点击停车图标启动打开运行时间稀释程序的方法。 </li><li>确保管子未封盖，并且移除板盖，并从顶端除去防尘盖。装载板，管和尖端到液体处理机器人的甲板上，如甲板布局所示。 </li><li>点击"播放"按钮运行稀释程序。选择正确数量的50μL提示。选择正确数量的300μL提示。等等12分钟进行运行。 </li></ol></li><li>从机器人取稀释板，盖上尖端，并回顾15 mL介质管。在30℃培养板5-6小时。 </li><li>开始第二次稀释前约1-2小时，请务必打开显微镜的孵育室。允许它们在℃或实验所需的温度下平衡。 </li><li>重复稀释步骤3.3 - 3.4，但将培养物稀释至0.01至0.02的OD 600，以便在琼脂糖载玻片上观察培养物。 </li><li>用金属冷冻密封盖住稀释板。 </li><li>使用离心机金属桶配件将稀释板在冰浴中超声处理30秒，使板悬浮在冰水中，以固定板（ 图2A ）。将超声处理的培养物从稀释板转移到平底板。标记4×96孔平底板1,2,3和4（ 图2B ）。 <ol><li>转让150＆＃181;将来自孔A01-D06的稀释板的L加入标记为1的板的孔C04-F09中。然后将150μL稀释板从孔A07-D12转移到标记为2的板的孔C04-F09中。然后转移150μL将孔E01-H06的稀释板放入标记为3的板的C04-F09孔中。最后将150μL的稀释板从孔E07-H12转移到标有4的板的C04-F09孔中。 </li></ol></li><li>转到步骤4，点燃琼脂。 </li></ol> 4.使用自动液体检测机器人检测琼脂<ol><li>从其加湿的无菌吸管盒中取出以4°CO / N（来自步骤2.19）储存的琼脂糖载玻片。 </li><li>如果需要，用干净的剃刀刀片修剪琼脂糖培养基的角落，以确保它们适合滑动室。 </li><li>从支架上卸下滑块。小心地将琼脂板放入舞台室底座的凹陷区域。 注意:确保或幻灯片的方法从实验到实验是一致的。 </li><li>检查以确保夹具与腔室底部齐平。如果弯曲，则幻灯片可能未完全就位在凹进的区域。将调平间隔件放入点样机器人的中心板位置。该间隔件为调平螺钉提供接触，使得滑动室可以与尖端平齐。 </li><li>将板放在桌子上，按照它们的象限。板1，2，3和4从左到右排列（ 图2B ）。 </li><li>布置提示，使内部24口井C04 - F09被占用4个空的提示盒。第五个盒子需要有一个尖端在C10位置，以及4个尖端，其端点在A01，A12，H01和H12位置被切断。这4个切断尖端为尖端板夹具提供了稳定性（ 图2C 和2D ）。 </li><li>从sl上卸下顶盖ide室安装。 </li><li>将第一个尖头冲头放入机器人控制点测试程序的起始位置。这应该在琼脂糖上打孔，以后将用于对齐原点坐标。将液位处理机器人上的板1放在第一象限位置。确保盖子已拆除，并继续检测程序。 </li><li>检查以确保所有斑点都存在。另外，等待〜30秒，让他们干燥。当斑点直径约为1mm时，程序可能会继续。将用过的尖端清空到生物危害容器中，并将新鲜的提示放在机器人上。换出第2象限盘1。 </li><li>重复第三个象限。并重复第四个象限。 </li><li>当斑点干燥时，更换滑盖室盖并翻转设备。 </li><li>用空气过滤器安装管路连接。 </li><li>将玻璃滑块放在腔室的顶部。 注意:此幻灯片对于reduci至关重要将热通量传递到琼脂中，并使冷凝物形成在室的客体盖滑动侧。不要忘记这个封面。根据显微镜结构，该盖滑动防止来自照明侧的加热在物体侧引起冷凝。 </li><li>放置风扇将热空气吹到室的物体侧。该风扇防止在盖板上形成冷凝。将通过起泡器的空气流量设定为10mL / min。 </li></ol> 5.在显微镜上运行ODELAY <ol><li>运行脚本"ODELAY_Microscope_Control.m"。 </li><li>点击"快门"打开传输的光快门，然后点击"对焦"按钮启动高相机速率（ 图3A ，红色箭头）。 </li><li>点击"去原点"，移动舞台，找到在琼脂中冲孔的原点。 </li><li>然后向右移动专注于区域E07发现的酵母细胞。 </li><li>返回到原点打孔并将其居中在视野中。 </li><li>通过按"设置"按钮（ 图3A ，蓝色箭头）将原点设置为该值。现在移动到位置H18并使用最靠近该位置的六角螺丝进行对焦。然后移动到位置L07并使用最靠近该位置的六角螺丝进行对焦。然后移动到位置E07并使用距离该位置最近的六角螺丝进行对焦。 </li><li>根据需要重复步骤5.5 - 5.7，直到这些位置保持对焦。 </li><li>检查中心的焦点和位于E12，H12，L12处的边缘。如果由Z值表示的焦点Z值大于±自动对焦范围（ 例如 ，将自动对焦范围设置为60μm，中心点的Z值大于±），则调整自动对焦范围40μm）。 </li><li>按复位按钮，这将激活按钮属性，然后按ODELAY（ 图3A ，绿色箭头）。选择保存数据的目录。确保有足够的驱动器空间可用。 注意:显微镜收集数据48小时，或直到程序关闭。 </li></ol> 6.处理ODELAY数据<ol><li>打开ODELAY_IPT.exe或使用脚本ODELAY_Image_Processing_Tool_v7.m脚本（ 图3C ）。 </li><li>准备一个* ODELAYExpDisc.xlsx excel电子表格。 </li><li>在单元格B1中命名实验。 </li><li>选择存储图像文件E07 - H18的图像目录。 </li><li>选择要写入数据的数据目录。 </li><li>将实验开始的日期写入单元格B04。使用格式MM / DD / YYYY。 </li><li>在C04单元中写入稀释时间。这个时间大约是在收集第一张图像之前的五分钟。使用格式HH:MMpm，其中HH为h，MM为最小。 </li><li>根据t加入菌株名称o源板（步骤3.1）。由于菌株被发现的方式，它们被重新排列在ODELAY琼脂糖载玻片上。电子表格B31-B126中的单元是源极板，而细胞C31 - C126是ODELAY琼脂平板中的斑点位置。 </li><li>然后按"过程数据"按钮，然后选择刚准备好的* ODELAYExpDisc.xlsx。 </li><li>根据用于处理数据的计算机系统等待16-24小时。 </li><li>处理图像时，会出现名为"ODELAY Well Data"的目录和文件"* _Index_ODELAYData.mat"。按"加载数据"按钮，选择刚生成的"* _Index_ODELAYData.mat"文件。这将加载刚刚处理的数据集。文件名中的"*"将根据输入到excel电子表格中的实验名称进行列出。 </li><li>加载数据后，使用底部找到的时间栏进行检查，点击图像正方形以查看生长曲线f或那个地点，或在左边的列表中找到一个很好的兴趣，然后加载该列表的图像。 </li><li>按"小提琴图"按钮生成人口增长参数的直方图。这将产生如图4或图6所示的曲线。 </li></ol>

<ol>
	<li>Zwietering, M. H., Jongenburger, I., Rombouts, F. M., van't Riet, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+of+the+bacterial+growth+curve.">Modeling of the bacterial growth curve.</a> Appl Environ Microbiol. 56 (6), 1875-1881 (1990).</li><li>Sellick, C. A., Campbell, R. N., Reece, 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=Galactose+metabolism+in+yeast-structure+and+regulation+of+the+leloir+pathway+enzymes+and+the+genes+encoding+them.">Galactose metabolism in yeast-structure and regulation of the leloir pathway enzymes and the genes encoding them.</a> Int Rev Cell Mol Biol. 269, 111-150 (2008).</li><li>Yoshikawa, K., 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=Comprehensive+phenotypic+analysis+for+identification+of+genes+affecting+growth+under+ethanol+stress+in+Saccharomyces+cerevisiae.">Comprehensive phenotypic analysis for identification of genes affecting growth under ethanol stress in Saccharomyces cerevisiae.</a> FEMS Yeast Res. 9 (1), 32-44 (2009).</li><li>Bryan, A. K., Goranov, A., Amon, A., Manalis, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+mass,+density,+and+volume+during+the+cell+cycle+of+yeast.">Measurement of mass, density, and volume during the cell cycle of yeast.</a> Proc Natl Acad Sci U S A. 107 (3), 999-1004 (2010).</li><li>Baryshnikova, A., 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=Quantitative+analysis+of+fitness+and+genetic+interactions+in+yeast+on+a+genome+scale.">Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.</a> Nat Methods. 7 (12), 1017-1024 (2010).</li><li>Costanzo, M., 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=The+genetic+landscape+of+a+cell.">The genetic landscape of a cell.</a> Science. 327 (5964), 425-431 (2010).</li><li>Collins, S. R., 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=Functional+dissection+of+protein+complexes+involved+in+yeast+chromosome+biology+using+a+genetic+interaction+map.">Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map.</a> Nature. 446 (7137), 806-810 (2007).</li><li>Zackrisson, M., 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=Scan-o-matic:+High-Resolution+Microbial+Phenomics+at+a+Massive+Scale.">Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale.</a> G3 (Bethesda). 6 (9), 3003-3014 (2016).</li><li>Bean, G. J., Jaeger, P. A., Bahr, S., Ideker, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+ultra-high-density+screening+tools+for+microbial+'omics'.">Development of ultra-high-density screening tools for microbial 'omics'.</a> PloS One. 9 (1), e85177 (2014).</li><li>Levy, S. F., Ziv, N., Siegal, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bet+hedging+in+yeast+by+heterogeneous,+age-correlated+expression+of+a+stress+protectant.">Bet hedging in yeast by heterogeneous, age-correlated expression of a stress protectant.</a> PLoS Biol. 10 (5), e1001325 (2012).</li><li>Herricks, T., 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=One-Cell+Doubling+Evaluation+by+Living+Arrays+of+Yeast.">One-Cell Doubling Evaluation by Living Arrays of Yeast.</a> ODELAY! G3 (Bethesda). 7 (1), 279-288 (2017).</li><li>Mast, F. D., Ratushny, A. V., Aitchison, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systems+cell+biology.">Systems cell biology.</a> J Cell Biol. 206 (6), 695-706 (2014).</li><li>Edelstein, A. D., 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=Advanced+methods+of+microscope+control+using+&#181;Manager+software.">Advanced methods of microscope control using &#181;Manager software.</a> J Biol Methods. 1 (2), e10 (2014).</li></ol>

作者没有什么可以披露的。

ODELAY测定法具有确保可重现和可靠的表型测量的几个关键点。第一个关键点是酵母培养物的一致准备。必须注意从对数生长收获酵母细胞。如果文化饱和，那么他们的群体异质性将会增加，这可能会混淆由遗传或环境（ 例如碳源）因素11引起的异质性。第二个关键点是媒体的一致准备。一般来说，应该产生大量的10X股票媒体解决方案，然后随着时间推移使库存效应最小化。通过重量制备培养基，尽可能通过确保琼脂糖的密度和琼脂糖的总体含水量得以密切监测，有助于提高培养基随时间的一致性。第三个关键点是最小化或消除琼脂糖我的任何机械变形直径。介质的机械变形通常会在分离琼脂糖与玻璃片时发生。与许多实验室技术一样，需要实践来掌握这一步骤。 如图4所示的滞后时间的变化通常与三个因素之一有关:琼脂糖介质的机械变形，模制琼脂厚度的变化或不稳定的光源。如果琼脂糖介质在斑点阵列上的Z高度变化，则高度变化可能会压倒自动对焦程序的范围，导致初始图像稍微偏离焦点。因此，检查中心点和点阵列边缘的多个点处的对焦高度，以确保自动对焦程序具有足够的Z范围来找到焦点。如果需要，使用自动对焦面板增加对焦范围并增加对焦步骤的数量。 第三个可能的条件可能导致焦点不足的离子是不稳定或闪烁的光源，这可能会破坏特定Z高度的计算焦点得分。在灯泡烧坏之前，钨卤素灯泡会很好地闪烁。在其中生长曲线在第一和第二时间点（ 图5A ）之间下降的一个实例中观察到不良焦点的影响，而相邻点不具有相同的浸渍（ 图 5B ）。在这种情况下，通过更换卤素卤素光源可以减轻对焦条件差。 在实践中，作者发现，为了减少100W钨卤素灯泡的闪烁，当显微镜被大量使用时，灯泡需要每500小时或大约每2个月更换一次。为了避免闪烁的灯泡引起的焦点不足，请经常更换钨卤素光源或用二极管光源替换卤素灯泡。一个在图6中示出了在倍增时间中显示低变化以及更均匀滞后时间的数据集的示例。该数据集采用二极管照明器，在执行自动对焦时可以随时间提供更稳定的照明。 虽然这里提到的优化媒体准备的许多观点可能看起来是显而易见的，但在文献中大多数大屏幕都不能很好地复制8,11 。因此，我们仔细地描述了培养物和琼脂糖介质的制备，以便可能产生更多可重现的表型筛选。 与基于固定的测定（如合成遗传数组）或Scan-O-Matic测定相比，ODELAY测定目前的吞吐量受到限制。虽然这些方法增加了测量的菌株数量，但它们缺乏解决单个细胞的能力因此不能测量我们在克隆酵母菌株内观察到的种群异质性。这个人口异质性的起源目前尚未得到理解，但是这里所示的技术和计算的合并提供了客观地解决潜在的细胞机制12的机会。 作者希望注意到，ODELAY目前仅针对特定的显微镜品牌和身体类型进行了优化。为其他显微镜系统修改ODELAY是直接的，但需要了解开源API 13 。然而，API和ODELAY脚本都被编写成易于适应于不同的系统和实验测定。 虽然ODELAY最初是为酵母开发的，但是我们已经能够在不改变的情况下利用它来观察耻垢分枝杆菌的生长。观察其他集落形成微生物是可能对提供的源代码进行修改11 。一般来说，ODELAY是一种强大且灵活的工具，用于比较在不同环境条件下生长的微生物和遗传扰动。

微生物的生长表型是对其给定环境条件的潜在遗传适应性的强指标。生长经典地分为3种不同的生长方式:滞后期，对数期和稳定期生长1 。每个生长阶段可以揭示依赖于各种环境和遗传条件的适应性的不同方面。例如，延迟时间或生物体在指数生长开始之前在滞后阶段中花费的时间长度可以指示生物体对改变的环境条件作出反应的能力2 。对数期生长期间的双倍增长是细胞适应度最常见的指标，揭示了生物体通过代谢和利用环境材料进行复制分裂能力的总体效率。固定阶段，在对数阶段之后的增长迅速减少，是健身的另一个指标，这是正常的在基于斑点的酵母生长测定中被用作生长终点。 目前有几种酵母生长测定可用，并且被认为是在酵母3,4,5中评价生长表型的标准方法。这些测定主要基于在固体或液体培养基中生长酵母的方法。在固体培养基上，菌落钉扎测定将少量细胞转移到具有针的固体琼脂上，使酵母细胞生长一段规定的时间。然后将殖民地成像，并在终端6比较其大小。这些集落钉扎测定已被证明是鲁棒和可扩展的，以产生全基因组屏幕。最近，使用平板扫描仪和单镜反射（SLR）相机的定期成像已被纳入这些测定中，以记录随时间的集落增长7,8， 9 。然而，这些装置的分辨率阻止它们检测单个细胞，因此，这些集落钉扎测定法不直接观察滞后时间，并且不能观察到生长到菌落中的各个细胞之间的变化。 基于液体的生长测定也已被用于进行全基因组筛选3 。用延时显微镜耦合液体生长测定显示遗传相同的个体细胞倍增时间的群体异质性，这为理解遗传调节和环境适应提供了重要的视角。然而，该测定不测量生长的其它方面，例如滞后时间和承载能力10 。在这里，我们提出一种方法来表征在固体培养基上形成菌落的微生物的所有三个生长阶段，使用我们的术语ODELAY 11 。 ODELAY由utili组成zing高通量延时显微镜记录在固体培养基上生长成菌落的单细胞的图像。生长在殖民地的单个细胞群体揭示了潜在的种群异质性，其不被其他较不敏感的测量（例如终端终点评分）检测到。我们展示酵母的方法，但是ODELAY可以应用于在明场显微镜中显示对比度的任何生物体。

<table border="0" cellpadding="0" cellspacing="0" width="1013">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Agarose UltraPure</td>
			<td style="width:131px;">ThermoFisher</td>
			<td style="width:119px;">16500500</td>
			<td style="width:413px;">Gel Temp 36C, Gel Strength (1%) 1.2g/sq cm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast Extract Peptone (YEP)</td>
			<td style="width:131px;">Fisher Scientific</td>
			<td style="width:119px;">BP1422-2</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Complete Suplement Mixture (CSM)</td>
			<td style="width:131px;">Fisher Scientific</td>
			<td style="width:119px;">MP114560222</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Polyethylene Glycol 3350 (av. mol. wt. 3000-3700)</td>
			<td style="width:131px;">SigmaAldrich</td>
			<td style="width:119px;">P2906</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast Strain BY4741</td>
			<td style="width:131px;">ThermoFisher</td>
			<td style="width:119px;">95400.BY4741</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast Strain BY4742</td>
			<td style="width:131px;">ThermoFisher</td>
			<td style="width:119px;">95400.BY4742</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">50mL Falcon tubes</td>
			<td style="width:131px;">Corning</td>
			<td style="width:119px;">430291</td>
			<td>1 case</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">15mL Falcon tubes</td>
			<td style="width:131px;">Corning</td>
			<td style="width:119px;">352096</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2 x 3 inch 1.0mm thick slides 1/2 gross</td>
			<td style="width:131px;">VWR</td>
			<td style="width:119px;">48382-179</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">96 well plate flat bottom</td>
			<td style="width:131px;">Corning&#160;</td>
			<td style="width:119px;">353072</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Hydra liquid handleing robot</td>
			<td style="width:131px;">Thermo</td>
			<td style="width:119px;">1096-DT-100</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Hamilton Microlab Star Liquid Handleing Robot</td>
			<td style="width:131px;">Hamilton</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">hydra 100 mL tips Extended Length DARTS</td>
			<td style="width:131px;">Thermo</td>
			<td style="width:119px;">5527</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Synergy H4 Plate Reader</td>
			<td style="width:131px;">Biotek</td>
			<td style="width:119px;">H4MLFAD</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Leica DMI6000 B Microscope</td>
			<td style="width:131px;">Leica</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Leica 10X/0.3NA objective</td>
			<td style="width:131px;">Leica</td>
			<td style="width:119px;">11506289</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">Hamamatsu ORCA Flash 4.0 Camera</td>
			<td style="width:131px;">Hamamatsu</td>
			<td style="width:119px;">C11440-22CU</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">MATLAB with image processing tool box</td>
			<td style="width:131px;">Mathworks</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">MicroManager</td>
			<td style="width:131px;">Open Imaging</td>
			<td style="width:119px;"></td>
			<td>https://micro-manager.org/</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:351px;">ODELAY Microscope Control (MATLAB scripts and GUI)</td>
			<td style="width:131px;"></td>
			<td style="width:119px;"></td>
			<td>www.aitchisonlab.com\ODELAY for Matlab scripts and software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">ODELAY Microscope Chamber</td>
			<td style="width:131px;"></td>
			<td style="width:119px;"></td>
			<td>www.aitchisonlab.com\ODELAY for Mechanincal Drawings</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:351px;">ODELAY Agar Molds</td>
			<td style="width:131px;"></td>
			<td style="width:119px;"></td>
			<td>www.aitchisonlab.com\ODELAY for mold drawings</td>
		</tr>
	</tbody>
</table>

odelay: a large-scale method for multi-parameter quantification of yeast growth

微生物的生长表型是其潜在遗传适应性的强指标，可以分为3个生长方式:滞后期，对数期和稳定期。每个生长阶段可以揭示与各种环境和遗传条件相关的适应性的不同方面。通常难以获得所有3个生长阶段的高分辨率和定量测量。在这里，我们提供一种详细的方法来表征固体培养基上所有3个生长阶段，使用称为酵母生活阵列的单细胞倍增评估（ODELAY）的测定法。 ODELAY使用延时显微镜量化生长在固体培养基上的菌落中的个体细胞的生长表型。这种方法可以直接观察生长在殖民地的遗传相同细胞中的每个生长参数的种群异质性。这种群体异质性为理解遗传和表观遗传调控以及对其的反应提供了独特的视角遗传和环境扰动。虽然使用酵母证明了ODELAY方法，但它可以用于通过明视野显微镜可见的任何集落形成微生物。

<html>在延时显微镜中生长的酵母的实例图像显示在图3B中 。处理延时图像后，比较酵母菌株BY4741＆BY4742的代表性数据集显示在图4中 。在该示例数据集中，板上不同位置之间的倍增时间几乎没有变化。如果琼脂糖培养基的制备不好，则在与琼脂糖凝胶的变形区域重合的斑点位置上，倍增时间和滞后时间都会明显的偏差。虽然倍增时间似乎相对均匀，但该示例显示了滞后时间测量的变化。更一致的数据集如图6所示。在该数据集中，滞后时间和倍增时间均匀。 / ftp_upload / 55879 / 55879fig1.jpg"/&gt; 图1:琼脂模组装。 琼脂模具的组分如（ A ）所示。如（ B ）所示组装底座，然后用小的夹子夹住底座。将更长的立柱放在基座（ C ）的空腔中，然后将滑块固定在模具上，如（ D ）所示。侧视图示出了用于使琼脂与玻片（ E ）一致分离所需的模具的角度和模切口的取向。注意拇指和食指的位置，以及与幻灯片（ F ）分离的琼脂直线，注意水平箭头。分离线应沿垂直方向均匀移动。 <a href="http://ecsource.jove.com/files/ftp_upload/55879/55879fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> ="jove_content"fo:keep-together.within-page ="1"&gt; <img alt="图2" class="xfigimg" src="/files/ftp_upload/55879/55879fig2.jpg" /> 图2:超声处理和检测方法。 在冰水中超声波处理板，并使用离心机斗架来帮助支撑板（ A ）。将平板从步骤3.8.1排出，以便点样到琼脂糖板（ B ）上。此外，安排这些尖端使得最左边的尖端盒在位置C10处具有一个尖端，然后将四个其它尖端切断，使得它们不会撞击板支架（ C ）。将剩余的提示放在四个盒子中，使内部24个提示位置被占用（ D ）。 <a href="http://ecsource.jove.com/files/ftp_upload/55879/55879fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 55879fig3.jpg"/&gt; 图3:ODELAY图形用户界面。 "ODELAY_Microscopecontrol.m"（ A ）的图形用户界面的屏幕截图。该界面允许监控摄像机并调整显微镜照明设置，以实现荧光和亮场模式。红色箭头指向对焦和传输按钮，激活相机快速获取图像并分别打开传输的光闸。蓝色箭头用于移动原点的舞台，然后使用"Go Origin"按钮和"Set"按钮设置原点。绿色箭头指向"重置"和"ODELAY !!!"将ODELAY图像模式重置为当前条件并启动ODELAY图像采集的按钮。点样后0,3,6和9小时在固体培养基上生长的酵母的延时图像（ B ）。 "ODELAY_IPT.m"的图形用户界面的屏幕截图<html> e ODELAY图像处理工具（ C ）。 <a href="http://ecsource.jove.com/files/ftp_upload/55879/55879fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图4" class="xfigimg" src="/files/ftp_upload/55879/55879fig4.jpg" /> 图4:ODELAY输出示例。 该数据集在YPD培养基上比较菌株BY4741和BY4742。这个数字是一个精心准备的琼脂糖幻灯片的例子;但是，自动对焦设置不是最佳的。从左到右的每一列中提供的数据是:殖民地区Log 2的承载能力;倍增时间，以分钟为单位;和滞后时间，以分钟为单位。在这个例子中，琼脂上的所有斑点的倍增时间都很顺利，少量的加倍的时间朝向色谱柱。然而，这个数据集的滞后时间有很大差异。_upload / 55879 / 55879fig4large.jpg"target ="_ blank"&gt;请点击此处查看此图的较大版本。 <img alt="图5" class="xfigimg" src="/files/ftp_upload/55879/55879fig5.jpg" /> 图5:增长曲线示例。 这个例子说明了较差的初始焦点可能导致估计的滞后时间（t lag ）增加（ A ），而相邻位置显示较短的滞后时间（ B ）。 t d是以min为单位的加倍时间，t lag是以分钟为单位的滞后时间。 <a href="http://ecsource.jove.com/files/ftp_upload/55879/55879fig5large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图6" class="xfigimg" src="/files/ftp_upload/55879/55879fig6.jpg" /> 图6:执行试验实验的例子。 一个e在使用二极管照明器替换钨卤素灯泡后测试BY4742应变的样本，并确保自动对焦设置正确。所有倍增时间看起来都很好重叠，滞后时间似乎是一致的。 <a href="http://ecsource.jove.com/files/ftp_upload/55879/55879fig6large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth at JoVE.com

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

我们提出了一种定量单个酵母细胞的生长表型的方法，它们使用称为酵母生活阵列的单细胞倍增评估（ODELAY）的延时显微镜在固体培养基上生长成菌落。可以直接观察和量化生长到菌落中的遗传相同细胞的群体异质性。

ODELAY:用于酵母生长多参数定量的大规模方法

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, ...

odelay-large-scale-method-for-multi-parameter-quantification-yeast

Research

JoVE Journal

Biology

8.1K 次观看.  Institute for Systems Biology. 我们提出了一种定量单个酵母细胞的生长表型的方法，它们使用称为酵母生活阵列的单细胞倍增评估（ODELAY）的延时显微镜在固体培养基上生长成菌落。可以直接观察和量化生长到菌落中的遗传相同细胞的群体异质性。 

视频: ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

Large-Scale Screens of Metagenomic Libraries

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation. Generating a streamlined procedure for creating and screening metagenomic libraries is therefore useful for efficient high-throughput investigations into the genetic and metabolic properties of uncultured microbial assemblages. Here, key protocols are presented on video, which we propose is the most useful format for accurately describing a long process that alternately depends on robotic instrumentation and (human) manual interventions. First, we employed robotics to spot library clones onto high-density macroarray membranes, each of which can contain duplicate colonies from twenty-four 384-well library plates. Automation is essential for this procedure not only for accuracy and speed, but also due to the miniaturization of scale required to fit the large number of library clones into highly dense spatial arrangements. Once generated, we next demonstrated how the macroarray membranes can be screened for genes of interest using modified versions of standard protocols for probe labeling, membrane hybridization, and signal detection. We complemented the visual demonstration of these procedures with detailed written descriptions of the steps involved and the materials required, all of which are available online alongside the video.

宏基因组库的大型屏幕

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation.  Generating a ...

科研

生物学

Batch Immunostaining for Large-Scale Protein Detection in the Whole Monkey Brain

Immunohistochemistry (IHC) is one of the most widely used laboratory techniques for the detection of target proteins in situ. Questions concerning the expression pattern of a target protein across the entire brain are relatively easy to answer when using IHC in small brains, such as those of rodents. However, answering the same questions in large and convoluted brains, such as those of primates presents a number of challenges. Here we present a systematic approach for immunodetection of target proteins in an adult monkey brain. This approach relies on the tissue embedding and sectioning methodology of NeuroScience Associates (NSA) as well as tools developed specifically for batch-staining of free-floating sections. It results in uniform staining of a set of sections which, at a particular interval, represents the entire brain. The resulting stained sections can be subjected to a wide variety of analytical procedures in order to measure protein levels, the population of neurons expressing a certain protein.

Large-scale immunodetection of target proteins across the entire primate brain is possible by employing novel tissue embedding and sectioning methods combined with the use of creative apparatus for batch staining of multiple free-floating sections at a given time.

在整个猴脑进行大规模蛋白质检测的批次免疫染色

Immunohistochemistry (IHC) is one of the most widely used laboratory techniques for the detection of target proteins in situ. Questions concerning the ...

Isolation and Large Scale Expansion of Adult Human Endothelial Colony Forming Progenitor Cells

This paper introduces a novel recovery strategy for endothelial colony forming progenitor cells (ECFCs) from heparinized but otherwise unmanipulated adult human peripheral blood within a mean of 12 days. After large scale expansion &gt;1x108 ECFCs can be obtained for further tests. Advantageously by using pHPL the contact of human cells with bovine serum antigens can be excluded. By flow cytometry and immunohistochemistry the isolated cells can be characterized as ECFC and their in vitro functionality to form vascular like structures can be tested in a matrigel assay. Further these cells can be subcutaneously injected in a mouse model to form functional, perfused vessels in vivo. After long term expansion and cryopreservation proliferation, function and genomic stability appear to be preserved. 3,4
This animal-protein free isolation and expansion method is easily applicable to generate a large quantity of ECFCs.

Endothelial colony forming progenitor cells (ECFCs) are a promising tool to study vascular homeostasis and repair.1,2 This paper introduces a novel animal-serum free method for isolation and expansion of ECFC from heparinised adult human peripheral blood with pooled human platelet lysate (pHPL) diminishing the risk of anti-bovine immunisation.

成人内皮细胞集落形成祖细胞的分离和大型规模扩张

This paper introduces a novel recovery strategy for endothelial colony forming progenitor cells (ECFCs) from heparinized but otherwise unmanipulated adult ...

Large Scale Zebrafish-Based In vivo Small Molecule Screen

Given their small embryo size, rapid development, transparency, fecundity, and numerous molecular, morphological and physiological similarities to mammals, zebrafish has emerged as a powerful in vivo platform for phenotype-based drug screens and chemical genetic analysis. Here, we demonstrate a simple, practical method for large-scale screening of small molecules using zebrafish embryos.

Large Scale Zebrafish-Based In vivo Small Molecule Screen

Zebrafish has emerged as a powerful in vivo platform for phenotype-based drug screens and chemical genetic analysis. Here, we demonstrate a simple, practical method for large-scale screening of small molecules using zebrafish embryos.

斑马鱼为基础的大型在体内小分子屏幕

Given their small embryo size, rapid development, transparency, fecundity, and numerous molecular, morphological and physiological similarities to ...

Computer-assisted Large-scale Visualization and Quantification of Pancreatic Islet Mass, Size Distribution and Architecture

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), and delta-cells (somatostatin) that are embedded in the exocrine tissues and comprise 1-2% of the entire pancreas. There is a close correlation between body and pancreas weight. Total beta-cell mass also increases proportionately to compensate for the demand for insulin in the body. What escapes this proportionate expansion is the size distribution of islets. Large animals such as humans share similar islet size distributions with mice, suggesting that this micro-organ has a certain size limit to be functional. The inability of large animal pancreata to generate proportionately larger islets is compensated for by an increase in the number of islets and by an increase in the proportion of larger islets in their overall islet size distribution. Furthermore, islets exhibit a striking plasticity in cellular composition and architecture among different species and also within the same species under various pathophysiological conditions. In the present study, we describe novel approaches for the analysis of biological image data in order to facilitate the automation of analytic processes, which allow for the analysis of large and heterogeneous data collections in the study of such dynamic biological processes and complex structures. Such studies have been hampered due to technical difficulties of unbiased sampling and generating large-scale data sets to precisely capture the complexity of biological processes of islet biology. Here we show methods to collect unbiased "representative" data within the limited availability of samples (or to minimize the sample collection) and the standard experimental settings, and to precisely analyze the complex three-dimensional structure of the islet. Computer-assisted automation allows for the collection and analysis of large-scale data sets and also assures unbiased interpretation of the data. Furthermore, the precise quantification of islet size distribution and spatial coordinates (i.e. X, Y, Z-positions) not only leads to an accurate visualization of pancreatic islet structure and composition, but also allows us to identify patterns during development and adaptation to altering conditions through mathematical modeling. The methods developed in this study are applicable to studies of many other systems and organisms as well.

Novel computer-assisted methods of large-scale procurement and analysis of immunohistochemically stained pancreatic specimens are described: (1) Virtual Slice capture of the entire section; (2) Mass analysis of large-scale data; (3) Reconstruction of 2D Virtual Slices; (4) 3D islet mapping; and (5) Mathematical analysis.

计算机辅助大型胰岛质量，粒度分布和结构的可视化和量化

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), ...

Yeast Colony Embedding Method

Patterning of different cell types in embryos is a key mechanism in metazoan development. Communities of microorganisms, such as colonies and biofilms also display patterns of cell types. For example, in the yeast S. cerevisiae, sporulated cells and pseudohyphal cells are not uniformly distributed in colonies. The functional importance of patterning and the molecular mechanisms that underlie these patterns are still poorly understood.
One challenge with respect to investigating patterns of cell types in fungal colonies is that unlike metazoan tissue, cells in colonies are relatively weakly attached to one another. In particular, fungal colonies do not contain the same extensive level of extracellular matrix found in most tissues . Here we report on a method for embedding and sectioning yeast colonies that reveals the interior patterns of cell types in these colonies. The method can be used to prepare thick sections (0.5 &mu;) useful for light microscopy and thin sections (0.1 &mu;) suitable for transmission electron microscopy. Asci and pseudohyphal cells can easily be distinguished from ovoid yeast cells by light microscopy , while the interior structure of these cells can be visualized by EM.
The method is based on surrounding colonies with agar, infiltrating them with Spurr's medium, and then sectioning. Colonies with a diameter in the range of 1-2 mm are suitable for this protocol. In addition to visualizing the interior of colonies, the method allows visualization of the region of the colony that invades the underlying agar.

A method for embedding yeast colonies allowing sectioning for light and electron microscopy. This protocol allows determination of the distribution of sporulated cells and pseudohyphal cells within colonies providing a new tool toward understanding the organization of cell types within a fungal community.

酵母殖民地嵌入方法

Patterning of  different cell types in embryos is a key mechanism in metazoan development. Communities of microorganisms, such as colonies and biofilms ...

Growth Assays to Assess Polyglutamine Toxicity in Yeast

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's disease, and Huntington's disease 1. Huntington's disease (HD) is caused by the abnormal expansion of a polyglutamine (polyQ) region within the protein huntingtin. The polyQ-expanded huntingtin protein attains an aberrant conformation (i.e. it misfolds) and causes cellular toxicity 2. At least eight further neurodegenerative diseases are caused by polyQ-expansions, including the Spinocerebellar Ataxias and Kennedy&#x2019;s disease 3.
The model organism yeast has facilitated significant insights into the cellular and molecular basis of polyQ-toxicity, including the impact of intra- and inter-molecular factors of polyQ-toxicity, and the identification of cellular pathways that are impaired in cells expressing polyQ-expansion proteins 3-8. Importantly, many aspects of polyQ-toxicity that were found in yeast were reproduced in other experimental systems and to some extent in samples from HD patients, thus demonstrating the significance of the yeast model for the discovery of basic mechanisms underpinning polyQ-toxicity. 
A direct and relatively simple way to determine polyQ-toxicity in yeast is to measure growth defects of yeast cells expressing polyQ-expansion proteins. This manuscript describes three complementary experimental approaches to determine polyQ-toxicity in yeast by measuring the growth of yeast cells expressing polyQ-expansion proteins. The first two experimental approaches monitor yeast growth on plates, the third approach monitors the growth of liquid yeast cultures using the BioscreenC instrument. 
Furthermore, this manuscript describes experimental difficulties that can occur when handling yeast polyQ models and outlines strategies that will help to avoid or minimize these difficulties. The protocols described here can be used to identify and to characterize genetic pathways and small molecules that modulate polyQ-toxicity. Moreover, the described assays may serve as templates for accurate analyses of the toxicity caused by other disease-associated misfolded proteins in yeast models.

This manuscript describes three complementary protocols for assessing the toxicity of polyglutamine (polyQ)-expansion proteins in the yeast Saccharomyces cerevisiae. These protocols can easily be modified to monitor the toxicity of other misfolded proteins in yeast.

生长实验，以评估在酵母中的多聚谷氨酰胺毒性

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's ...

Multi-parameter Measurement of the Permeability Transition Pore Opening in Isolated Mouse Heart Mitochondria

The mitochondrial permeability transition pore (mtPTP) is a non specific channel that forms in the inner mitochondrial membrane to transport solutes with a molecular mass smaller than 1.5 kDa. Although the definitive molecular identity of the pore is still under debate, proteins such as cyclophilin D, VDAC and ANT contribute to mtPTP formation. While the involvement of mtPTP opening in cell death is well established1, accumulating evidence indicates that the mtPTP serves a physiologic role during mitochondrial Ca2+ homeostasis2, bioenergetics and redox signaling 3.
mtPTP opening is triggered by matrix Ca2+ but its activity can be modulated by several other factors such as oxidative stress, adenine nucleotide depletion, high concentrations of Pi, mitochondrial membrane depolarization or uncoupling, and long chain fatty acids4. In vitro, mtPTP opening can be achieved by increasing Ca2+ concentration inside the mitochondrial matrix through exogenous additions of Ca2+ (calcium retention capacity). When Ca2+ levels inside mitochondria reach a certain threshold, the mtPTP opens and facilitates Ca2+ release, dissipation of the proton motive force, membrane potential collapse and an increase in mitochondrial matrix volume (swelling) that ultimately leads to the rupture of the outer mitochondrial membrane and irreversible loss of organelle function.
Here we describe a fluorometric assay that allows for a comprehensive characterization of mtPTP opening in isolated mouse heart mitochondria. The assay involves the simultaneous measurement of 3 mitochondrial parameters that are altered when mtPTP opening occurs: mitochondrial Ca2+ handling (uptake and release, as measured by Ca2+ concentration in the assay medium), mitochondrial membrane potential, and mitochondrial volume. The dyes employed for Ca2+ measurement in the assay medium and mitochondrial membrane potential are Fura FF, a membrane impermeant, ratiometric indicator which undergoes a shift in the excitation wavelength in the presence of Ca2+, and JC-1, a cationic, ratiometric indicator which forms green monomers or red aggregates at low and high membrane potential, respectively. Changes in mitochondrial volume are measured by recording light scattering by the mitochondrial suspension. Since high-quality, functional mitochondria are required for the mtPTP opening assay, we also describe the steps necessary to obtain intact, highly coupled and functional isolated heart mitochondria.

A spectrofluorometric protocol for the measurement of the mitochondrial permeability transition pore opening in isolated mouse heart mitochondria is presented here. The assay involves the simultaneous measurement of mitochondria Ca2+ handling, mitochondrial membrane potential and mitochondrial volume. The procedure for obtaining high-quality and functional heart mitochondria is also described.

小鼠离体心肌线粒体通透性转换孔开放中的多参数测量。

The mitochondrial permeability transition pore (mtPTP) is a non specific channel that forms in the inner mitochondrial membrane to transport solutes with ...

Infinium Assay for Large-scale SNP Genotyping Applications

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina&#39;s panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.

A protocol is described that uses Illumina&#39;s Infinium assays to perform large-scale genotyping. These assays can reliably genotype millions of SNPs across hundreds of individual DNA samples in three days. Once generated, these genotypes can be used to check for associations with a variety of different diseases or phenotypes.

Infinium检测的大型SNP基因分型应用

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of ...

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.&#160; Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. Utilizing normal-phased liquid chromatography coupled to high-resolution mass spectrometry with polarity switching and a rapid duty cycle, we describe a protocol to analyze the polar metabolic composition of biological material with high sensitivity, accuracy, and resolution.

敏感，大规模定量代谢组学的策略

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting ...