Name: highly multiplexed, super-resolution imaging of t cells using madstorm
Uploaded: 2017-06-24T12:30:00.000+00:00
Duration: 8 min 43 s
Description: Watch this Scientific Journal Video about Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM at JoVE.com

感谢吴旭峰访问STORM显微镜。这项研究得到了国家癌症研究所（NCI）癌症研究中心和国家心肺血液研究所（NHLBI）的校内研究计划的支持。

注意:使用前请咨询所有相关材料安全数据表（MSDS）。本议定书中使用的几种化学物质是有毒和致癌的。执行协议时，请使用所有适当的安全措施，包括使用工程控制（通风橱，手套箱）和个人防护装备（安全眼镜，手套，实验室外套，全长裤，闭式脚趾鞋）。 1.活化T细胞复制成像<ol><li>使用Alexa 647抗体标记试剂盒与Alexa-647（A647）染料直接缀合抗体。遵循制造商提供的标签协议。 注意:在此步骤之前，建议在1x PBS中透析抗体溶液以提高抗体标记效率。 </li><li>在20,800 rcf下旋转标记抗体5 min，收集上清液以除去聚集的抗体。 </li><li> 荧光纳米金刚石涂层盖玻片的制备 <ol&gt; <li>用250μL的0.01％聚-L-赖氨酸（PLL）涂覆8孔盖玻片室（参见试剂/材料清单）15分钟，抽出并在65℃下干燥30分钟。 （干燥前不要冲洗） </li><li>在1x PBS中准备100 nm FND的稀释液。测试各种稀释液以确保在步骤1.2.7（我们使用制造商提供的FND的1:200稀释度）的每个视野中有足够的FNDs。 </li><li>涡旋稀释的FNDs 1分钟。 </li><li>在高功率设置下将FND上清液超声处理30秒。 </li><li>将超声处理的FND上清液在室温下在PLL涂覆的8孔盖玻片室中孵育30分钟。 </li><li>用1x PBS洗5次，并在TIRF显微镜上使用647nm激光激发可视化FND涂层室。理想情况下，如果在步骤1.2.2中对FND进行了适当的稀释，我们可以在视场中看到4-10个单独的FND（我们使用的是具有256 x 256个相机像素设置的100X物镜，以获得61 x 61μm的视野）与在在成像领域的每个象限中存在至少一个FND。如果FND似乎是聚类的（ 即 ，具有比周围FND显着更高的信号的FND和大于200nm的点扩散函数），则以6,800 rcf离心FNDs 1分钟，并使用FND上清液重复涂覆程序。 </li><li>在每个孔中加入250μl抗CD3抗体（10μg/ mL），并在37℃下孵育1小时，或在4℃下孵育过夜。 </li><li>取出溶液并加入1x PBS 30秒。重复此洗涤步骤5次（洗5次）。 </li></ol></li><li> 激活Jurkat T细胞 <ol><li>将1 ml Jurkat T细胞以800 rcf转染6 min，并重悬于300μl1x HBS溶液中。理想情况下，Jurkat T细胞在纺丝前的浓度应为0.5-1.0×10 6个细胞/ ml。 1 HBS溶液由前述22所述的HEPES缓冲盐水与1％牛血清白蛋白组成。 </li><li>加入150μL的每个孔中的1 HBS溶液，并在37℃孵育15分钟。 </li><li>向每个孔中加入50μL重悬浮的Jurkat T细胞，37℃孵育3分钟。 </li><li>向每个孔中加入300μL的4％对甲醛并在37℃下孵育30分钟。 </li><li>用1x PBS洗3次。 </li><li>通过在室温下加入250μL0.1％Triton-X溶液5分钟使细胞渗透。 </li><li>用1x PBS洗3次。 </li><li>在室温下向每个孔中加入250μL1％的在PBS中的1％鱼明胶溶液30分钟。 </li><li>用1x PBS洗3次。 </li></ol></li><li> 使用madSTORM成像激活Jurkat T细胞 <ol><li>在室温下向固定细胞中加入200μL0.1〜0.5μg/ mL的标记抗体1小时。 </li><li>用1x PBS洗5次。 </li><li>加入1ml的STORM缓冲液，并用玻璃盖玻片覆盖室，以限制暴露在空气中。之前已经描述了STORM缓冲区10 。我们建议马King新的STORM缓冲液，用于每轮成像，并将STORM缓冲液以20,800 rcf旋转2分钟以除去沉淀物。 </li><li>在TIRF模式下使用低647 nm激光功率，在视野中定位至少有3个FND的染色细胞。为了帮助定位FND，可以使用568 nm激光的伴随激励来提高FND信号的亮度。 注意:2.1节中描述的平均基准校正的性能随着更多的FND的增加而改善。 </li><li>增加647 nm激光功率并获取图像。我们通常以200 ms曝光，125 mW 647 nm激光，100X TIRF物镜（1.49 NA），100X EM增益（16位5 MHz，转换增益1））获取10,000帧。以前已经描述了我们的成像设置的细节10 。 </li><li>用1x TBS洗5次。 </li><li>加1 ml of洗脱缓冲液（3.5M MgCl 2，20mM PIPES，0.1％Tween-20，pH6.5），并在室温下孵育1分钟。 </li><li>重复洗脱3次。 （必须检查每种使用的抗体的精确洗脱条件和去除信号所需的洗脱漂洗次数）。 </li><li>用1x TBS洗3次，加入1ml 1x PBS。 </li><li>光漂白剂使用高功率（125mW）的647nm激光器，在405mW的405nm激光下以黑暗状态光活化A647染料。等待直到来自未洗脱的抗体的所有剩余信号被光漂白。通常这需要2-5秒的激光曝光。在洗脱和漂白后，使用1.3.5中的STORM设置获取样品图像（〜100帧），以确认信号的去除。 我们通常使用这种方法去除99.8％的信号。我们建议在madSTORM使用前测试每种抗体的洗脱效率，如前所述。 </li><li>加入250μL4％的多聚甲醛15 min。这个事件在细胞中固定分子的反向交联。 </li><li>用1x PBS洗3次。 </li><li>重复步骤1.3.1-1.3.12以顺序标记多个目标。 图1显示了使用madSTORM获得的激活的Jurkat T细胞中的多个分子的合成图像。 </li></ol></li></ol> 2.多路复用图像堆栈的漂移校正和对准<ol><li> 漂移校正的madSTORM图像堆栈 <ol><li>使用ImageJ打开图像。我们建议在ImageJ打开之前将图像文件转换为TIFF格式。使用矩形ROI来选择单个FND。播放时间流逝以确保FND在图像堆栈的每个帧中都可见。在ThunderSTORM插件中使用运行分析来定位FND。对于2.1.5中描述的平均基准校正方法，重要的是将单个FND定位在每个图像帧中（ 即确定的峰值数应为e等于帧数）。 </li><li>如果在每个帧中未识别到FND，请选择另一个FND。如果多个峰位于单个帧中，请删除偏离最早峰的峰。 </li><li>对图像堆叠中的每个FND重复2.1.2。请记住，漂移校正过程中不应包含一些FND，因此它们可以作为步骤2.1.7中所述的漂移校正精度的独立量规。 </li><li>为了更快，更精确的漂移校正，请使用ThunderSTORM中包含的互相关或基准校正算法来校正FND图像。通常，我们使用100个箱，5个放大倍率和0.1个轨迹平滑因子进行互相关，10个最大距离，0.1分钟标记可见度比和0.01个轨迹平滑因子进行基准校正。交叉相关和基准校正将产生一个可应用于其他FND的校正文件，以测试漂移校正精度。 </li><li>对于更严格，更精确的漂移校正，使用如前所述的平均基准校正（AFC）算法10 。该过程不需要优化参数，并且产生比SMLM定位算法预测的更高的定位精度。然而，平均漂移校正需要至少4个FND，并且将FND定位在图像堆栈的每个帧中。包含更多的FND，AFC漂移校正表现更好，因为大量的局部FND将减少给定帧中异常值峰值的失真效应。 </li><li>如前所述，使用ThunderSTORM对图像堆栈内的所有点扩散函数进行本地化。我们通常使用100nm的像素尺寸，每A / D计数为4.28的光电子，基准电平A / D计数为100，EM增益为100，PSF:集成高斯定位，5像素拟合半径，最大似然拟合方法和1.3像素初始西格玛</li><li>将从FND获取的漂移校正因子应用于整个图像堆栈的本地化。目视检查最终图像以确保正确的漂移校正（ 图2 ）。所产生的漂移校正因子应在AFC程序中未包含的FND上独立测试，以测量漂移校正精度的水平。漂移校正的独立FND的精度应接近从步骤2.1.6中使用的定位算法计算的平均精度/不确定度值。 </li><li>对于顺序标记的抗体的madSTORM图像堆叠重复步骤2.1.1-2.1.7。请记住，在每个madSTORM映像堆栈中对同一组FND进行本地化对于以下对齐过程至关重要。 </li></ol></li><li> 对齐madSTORM图像 <ol><li>计算每个madSTORM图像中漂移校正的FND的质心位置。要做到这一点，找到平均x和y轴po每个本地化FND的情景，并平均每个madSTORM图像中所有FND的平均x和y位置。以前已经描述了该步骤的详细算法10 。使用FND基准标记的质心位置对齐顺序的madSTORM图像。要执行对齐，通过从第一个madSTORM图像中减去第二个madSTORM图像中的FND的重心位置来计算两个本地化的madSTORM图像之间的偏移量。然后从第二个madSTORM映像中的所有本地化中减去偏移量。 </li><li>我们建议使用第一个madSTORM图像作为参考图像，并在第一和第三，第一和第四等之间重复此对齐步骤。通过测量未包括在对齐过程中的FND之间的偏移来测试对准精度。大的偏移可能表示在计算顺序的madSTORM图像的质心位置时使用不同的FND组。 </li><li>如果是这样，步骤2.2.1-2.2.2 shou使用同一组FND重复进行对齐。 注意:提供了AFC漂移校正和校准程序的自定义代码。 </li></ol></li></ol>

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我们没有什么可以披露的。

madSTORM中的顺序多路复用，漂移校正和校准程序允许在单元格中精确，高度多路复用异构结构的可视化。 10此外，madSTORM避免了多色STORM的局限性，如非远红色染料9,12的色差和次优照相切换/发射性能。由于洗脱步骤显着降低了来自顺序结合的抗体的空间干扰，所以可以使用madSTORM进行细胞样品的重复成像，超过先前技术9,15,21所达到的6-10轮复用成像。此外，顺序洗脱和染色步骤不限于SMLM，并且可以用于其它成像技术，例如共聚焦显微镜，SIM和双光子显微镜。但是，鉴于疯狂TORM是一种连续的免疫染色技术，该技术受到每个靶向分子抗体的可用性的限制。应仔细测试每种抗体，以确保特异性，标记效率和洗脱能力。 选择了madSTORM的采集设置，以最大限度地发现各个照片切换事件的检测，使我们能够实现2.5nm的平均定位精度。然而，高精度以牺牲时间为代价，如前所述，对于每一轮的madSTORM成像要求〜3 h。为了以较低的定位精度（5-10 nm）进行更快的图像采集，建议使用更短的曝光时间和更高的EM增益（ 例如 20 ms曝光，300X EM增益，16位17 MHz，转换增益3）。此外，多色成像（ 例如， Atto-488，Alexa-568和Alexa-647nm）可以对每一轮的madSTORM成像进行，以增加复用的规模，尽管wi这是由于色差引起的对准精度的降低。 我们已经使用该协议成功地执行了25轮的madSTORM成像。由于整个过程是用安装在显微镜载物台上的盖玻片室进行的，所以重要的是将盖玻片室固定在相同的位置。为此，可以使用自动对焦模式，并使用金属夹将显微镜平台安装在显微镜平台上。如果出现显着的阶段漂移，则使用FND基准标记的已知位置来重新定位细胞样本。 对齐的madSTORM图像的同时可视化可能是具有挑战性的。要同时查看7个或更少的madSTORM图像，请使用ImageJ中的"颜色/合并"通道创建伪彩色合成图像。对于8个或更多图像，建议将madSTORM图像放大到不同的组，将每个组合并为一个合成图像，并将单个LUT颜色应用于每个合成图像。 <p class="jove_content"&gt;我们使用100 nm的氮空位中心纳米金刚石，因为它们的亮度和粘附到PLL涂覆的盖玻片上。小于80nm的FND不适用于PLL涂覆的盖玻片，当使用647nm激光激发时，大于100nm的FND显着比Alexa-647染料亮，限制了Alexa-647发射的相机采集设置的优化。如果100 nm氮素空位中心FND不适合您的成像设置，我们建议您尝试使用不同的FND尺寸或颜色。或者，纳米金颗粒或荧光珠可用作基准标记，但对于2.110中下面使用的平均点校正程序不是最佳的。最后，对于NV -空缺FND，通过施加静磁场23 ，发射强度可以原位降低高达约50％。强度的降低大致为线性，高达〜500高斯，在这一点上有效t饱和。在实践中，通过使永磁体从顶部更接近显微镜载玻片，可以将视野中的金刚石的强度降低到期望的程度。 最后，我们优化了洗脱缓冲液，以去除靶向T细胞微团簇分子成分的抗体。然而，由于微管，线粒体，F-肌动蛋白，波形蛋白和其他分子结构已经使用这种技术成像，所以madSTORM不限于TCR微团簇。对于靶向其他细胞区室的抗体，可能需要额外的步骤来破坏表位结合，例如更高的温度，更低的pH值和更长的洗脱缓冲液的孵育。相反，洗脱缓冲液可以不用Tween-20使用来靶向敏感的膜结构，防止非离子相互作用的破坏。我们预计在未来的实验中洗脱缓冲液组合物将针对个体抗体t进行定制o优化洗脱效率和样品保存。此外，除了在活化的T细胞中的应用之外，对于包括体外分子复合物，不同细胞类型和组织切片的其它系统，madSTORM可能是可行的。需要针对每个目标系统调整madSTORM方案的各种参数，如固定，透化，抗体染色和洗脱缓冲液组成。

已经开发了各种超分辨率显微技术来克服光学显微镜（〜200nm）的衍射极限。其中包括一类称为单分子定位显微术（SMLM）的技术，包括光激活定位显微镜（PALM）和随机光学重建显微镜（STORM）。 SMLM技术共享使用可在on（荧光）和off（暗/光切换）状态之间切换的荧光团，允许来自单分子1,2,3的荧光的顺序定位。 由于其与商业上可获得的染料和显微镜的兼容性，STORM（dSTORM）直接成为广泛采用的SMLM技术。 dSTORM可以定期实现〜10 nm的定位精度，定义为计算衍射中心的不确定度离子限制点扩散函数（PSF）。然而，尽管使用本地化算法估计的高精度5,6,7 ，单个分子的实际位置的准确确定受到一些问题的阻碍。首先，在图像采集期间显微镜平台的机械运动增加了定位精度的显着不确定性。由于SMLM图像通过数千个延时帧获得，显微镜平台的纳米尺度运动可能会显着损害最终超分辨率图像8的精度。为了补偿图像采集期间的阶段移动，通常基于来自图像本身（互相关）或来自基准标记（基准校正）的顺序定位的基于回归的拟合来估计阶段漂移。 Howev呃，这些方法需要优化每个图像堆叠的多个参数，并且不能在诸如机械振动的短时间尺度上考虑阶段运动。金纳米颗粒和多色荧光珠已经用作SMLM中的基准标记，但它们不是光稳定的，并且在漂移校正后比使用的氮空位中心荧光纳米钻石（FND）显着降低精度在madSTORM 10 。 除了衍射极限外，光学显微镜进一步受光谱限制。多个目标的同时可视化需要具有非重叠光谱特征的荧光探针，通常将基于荧光的光学显微镜限制为6种颜色，并将SMLM限制为2-3色4,11,12。此外，非线性色差导致多色图像的偏移，w需要使用多色基准标记8,13的广泛对准程序。为了克服这些限制，先前的研究已经使用重复光漂白或连续结合的荧光团14,15,16,17,18,19的化学淬灭成像了多个靶。虽然这些方法可以克服显微镜的光谱极限，但是已知荧光漂白是有毒的方法20 ，而延长的漂白或猝灭可能引起不期望的副作用，例如交联失去。此外，荧光探针的积累可导致样品中结合位点的空间阻断，防止表位的大规模复用和强大的靶向。为了避免这种空间干扰，最近的一个小编使用随机交换自由扩散的蛋白质片段21实现多路复用。尽管这种方法允许细胞结构的密集标记，但是它需要广泛的生物化学制备以分离肽片段，不能定位单分子位置，并且不容易利用市售的探针进行大规模复制。我们提供一个详细的视频协议，描述荧光抗体的顺序结合和洗脱，用于复用，抗体大小限制的dSTORM（madSTORM）成像，以及使用荧光纳米金刚石来实现精确的漂移校正和对准。

<table><tbody><tr><td>8 well coverslip chamber</td><td>Lab-tek</td><td>155409</td><td></td></tr><tr><td>0.1% Poly-L-Lysine solution</td><td>Sigma-Aldrich</td><td>P8920</td><td></td></tr><tr><td>NV-100 nm Fluorescent Nano-diamond</td><td>Adamas</td><td>Red FND</td><td></td></tr><tr><td>anti-CD3&amp;epsilon; antibody</td><td>BD Biosciences</td><td>555329</td><td></td></tr><tr><td>Bovine serum albumin, Fraction V</td><td>KSE Scientific</td><td>98-100P</td><td></td></tr><tr><td>Triton-X</td><td>Sigma-Aldrich</td><td>T9284</td><td></td></tr><tr><td>10% Paraformaldehyde</td><td>EMS</td><td>15712</td><td>Carcinogen</td></tr><tr><td>Gelatin from fresh water fish skin</td><td>Sigma-Aldrich</td><td>G7041</td><td></td></tr><tr><td>Alexa 647 antibody labeling kit</td><td>Thermo Fisher</td><td>A20186</td><td></td></tr><tr><td>Magnesium Chloride hexahydrate</td><td>Sigma-Aldrich</td><td>138924</td><td></td></tr><tr><td>PIPES</td><td>Sigma-Aldrich</td><td>P6757</td><td></td></tr><tr><td>Tween-20</td><td>Fisher Scientific</td><td>BP337-500</td><td></td></tr><tr><td>2-Mercaptoethanol</td><td>Sigma-Aldrich</td><td>M7154</td><td>Highly toxic, air sensitive</td></tr><tr><td>Cysteamine</td><td>Sigma-Aldrich</td><td>30070</td><td>Highly toxic</td></tr><tr><td>Cyclooctatetraene 98%</td><td>Sigma-Aldrich</td><td>138924</td><td>Highly toxic, air sensitive</td></tr><tr><td>10x PBS</td><td>KD Medical</td><td>RGF-3210</td><td></td></tr><tr><td>10x TBS</td><td>KD Medical</td><td>RGF-3385</td><td></td></tr></tbody></table>

highly multiplexed, super-resolution imaging of t cells using madstorm

使用单分子定位显微镜的成像异质细胞结构受到定位精度和复用能力不足的阻碍。使用荧光纳米金刚石基准标记，我们描述了在单分子定位显微镜中获得高精度所需的漂移校正和校准程序。另外，描述了新的复用策略madSTORM，其中使用荧光抗体的顺序结合和洗脱将多个分子靶向相同的细胞。在活化的T细胞上证明了madSTORM可视化在称为T细胞受体微团簇的膜结合的多蛋白结构内的不同组分的位置。另外，讨论了madSTORM作为多蛋白结构可视化的一般工具的应用。

使用顺序洗脱和染色方法在活化的Jurkat T细胞中产生微团簇和其他结构的多重madSTORM图像（ 图1 ，检查图对齐）。每个伪彩色图像表示在步骤1.1.1至1.3.13中获取的一轮madSTORM成像。如前所述10 ，应该对来自先前的非洗脱抗体的残留信号进行监视，以避免复用目标之间的串扰。此外，随着洗脱效率可以在抗体之间变化，顺序复用的顺序应该从最佳到最差的洗脱抗体排列，以使表位的空间阻塞最小化。 如图2所示 ， 图1中最后的madSTORM图像已经使用AFC和FND基准标记进行漂移和校准。 图2A ， 2B ）和激活的Jurkat T细胞（ 图2C ， 2D ）的定位的AFC。使用所提供的算法，如步骤2.1.1-2.1.8中所述进行AFC漂移校正。首先，建议漂移校正后图像的目视检查（ 图2C ），以确保漂移校正算法的正确应用。其次，推荐确定X轴和Y轴的定位标准偏差，以确认AFC实现的精度。如前所述10 ，AFC通常通过各种定位算法产生比预期更好的精度。 <img alt="图1" class="xfigimg" src="/files/ftp_upload/55997/55997fig1.jpg" /> 图1 :( A） </强&gt;）激活的Jurkat T细胞，使用多次madSTORM成像顺序成像。 LAT（红色），pLAT-Y171（品红色），pLAT-Y191（粉红色），pLAT-Y226（紫色），PLCγ1（浅蓝色），pSLP76-Y128（绿色），pSRC-Y416（aqua），pTCRζ-Y142蓝色），TOM20（黄色），α青霉素（橙色），ZAP70（棕色）。刻度棒=2.5μm。 （ B ）A中盒装区域的扩展图像。比例尺= 500nm。 <a href="http://ecsource.jove.com/files/ftp_upload/55997/55997fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图2" class="xfigimg" src="/files/ftp_upload/55997/55997fig2.jpg" /> 图2:在平均基准校正后，在30,000次图像帧（ A ）之前和（ B ）漂移校正后，单个FND的SMLM图像。刻度棒= 20nm（A和B）。激活的Jurkat T细胞染色的SMLM图像抗磷酸化SLP76（Y128）抗体和FND基准标记（ C ）之前和（ D ）漂移校正后的平均基准校正。比例尺= 2μm。 <a href="http://ecsource.jove.com/files/ftp_upload/55997/55997fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM at JoVE.com

Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

我们展示了使用荧光标记抗体的顺序结合和洗脱以单分子精确度在异质纳米结构内成像多个分子的方法。

使用madSTORM进行高分辨率，超分辨率的T细胞成像

Imaging heterogeneous cellular structures using single molecule localization microscopy has been hindered by inadequate localization precision and ...

highly-multiplexed-super-resolution-imaging-of-t-cells-using-madstorm

Universidad San Sebastian

Research

JoVE Journal

Immunology and Infection

7.3K 次观看.  National Institutes of Health. 我们展示了使用荧光标记抗体的顺序结合和洗脱以单分子精确度在异质纳米结构内成像多个分子的方法。 

视频: Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins

Signaling is initiated through the T Cell Receptor (TCR) when it is engaged by antigenic peptide fragments bound by Major Histocompatibility Complex (pMHC) proteins expressed on the surface of antigen presenting cells (APCs). The TCR complex is composed of the ligand binding TCR&alpha;&beta; heterodimer that associates non-covalently with CD3 dimers (the &#949;&delta; and &#949;&gamma; heterodimers and the &zeta;&zeta; homodimer)1. Upon engagement of the receptor, the CD3 &zeta; chains are phosphorylated by the Src family kinase, Lck. This leads to the recruitment of the Syk family kinase, Zap70, which is then phosphorylated and activated by Lck. After that, Zap70 phosphorylates the adapter proteins LAT and SLP76, initiating the formation of the proximal signaling complex containing a large number of different signaling molecules2. 
The formation of this complex eventually results in calcium and Ras-dependent transcription factor activation and the consequent initiation of a complex series of gene expression programs that give rise to T cell differentiation2. TCR signals (and the resulting state of differentiation) are modulated by many other factors, including antigen potency and crosstalk with co-stimulatory/co-inhibitory, chemokine, and cytokine receptors 3-4. Studying the spatial and temporal organization of the proximal signaling complex under various stimulation conditions is, therefore, key to understanding the TCR signaling pathway as well as its regulation by other signaling pathways.
One very useful model system to study signaling initiated by the TCR at the plasma membrane in T cells is glass-supported lipid bilayers, as described previously5-6. They can be utilized to present antigenic pMHC complexes, adhesion, and co-stimulatory molecules to T cells-serving as artificial APCs. By imaging the T cells interacting with the lipid bilayer using total internal reflection fluorescence microscopy (TIRFM), we can restrict the excitation to within 100 nm of the space between the glass and the cell surface 7-8. This allows us to image primarily the signaling events occurring at the plasma membrane. As we are interested in imaging the recruitment of signaling proteins to the TCR complex, we describe a two-camera TIRF imaging system wherein the TCR, labeled with fluorescent Fab (fragment antigen binding) fragments of the H57 antibody (purified from hybridoma H57-597, ATCC, ATCC Number:HB-218) which is specific for TCR&beta;, and signaling proteins, tagged with GFP, may be imaged simultaneously and in real time. This strategy is necessary due to the highly dynamic nature of both the T cells and of the signaling events that are occurring at the TCR. This imaging modality has allowed researchers to image single ligands 9-11 as well as recruitment of signaling molecules to activated receptors and is an excellent system to study biochemistry in-situ12-16.

The compartmentalization of proteins either within the plasma membrane or into intracellular locations is one regulatory mechanism that can greatly influence signaling outcomes; hence, to understand signaling it is important to study the spatial and temporal behavior of the proteins involved. We describe here a TIRF microscopy based system to study signal transduction in T cells, but is broadly applicable.

一个实时，同步成像的TCR和其相关的信号转导蛋白的T​​IRF显微镜技术

Signaling is initiated through the T Cell Receptor (TCR) when it is engaged by antigenic peptide fragments bound by Major Histocompatibility Complex ...

科研

免疫与感染

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

The signaling and function of a cell are dictated by the dynamic structures and interactions of its surface receptors. To truly understand the structure-function relationship of these receptors in situ, we need to visualize and track them on the live cell surface with enough spatiotemporal resolution. Here we show how to use recently developed Lattice Light-Sheet Microscopy (LLSM) to image T-cell receptors (TCRs) four-dimensionally (4D, space and time) at the live cell membrane. T cells are one of the main effector cells of the adaptive immune system, and here we used T cells as an example to show that the signaling and function of these cells are driven by the dynamics and interactions of the TCRs. LLSM allows for 4D imaging with unprecedented spatiotemporal resolution. This microscopy technique therefore can be generally applied to a wide array of surface or intracellular molecules of different cells in biology.

The goal of this protocol is to show how to use Lattice Light-Sheet Microscopy to four-dimensionally visualize surface receptor dynamics in live cells. Here T cell receptors on CD4+ primary T cells are shown.

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

The signaling and function of a cell are dictated by the dynamic structures and interactions of its surface receptors. To truly understand the ...

生物化学

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is an effective methodology for tumor evaluation that improves the understanding of the tumor microenvironment. The visualization of protein expression in formalin-fixed, paraffin-embedded&#160;tissues is achieved when a specific fluorophore is annealed to an antibody-bound barcode via complementary oligonucleotides and then sample imaging is performed; indeed, this method allows for the use of customizable panels of more than 40 antibodies in a single tissue staining reaction. This method is compatible with fresh frozen tissue, formalin-fixed, paraffin-embedded tissue, cultured cells, and peripheral blood mononuclear cells, meaning that researchers can use this technology to view a variety of sample types at single-cell resolution. This method starts with a manual staining and fixing protocol, and all the antibody barcodes are applied using an antibody cocktail. The staining fluidics instrument is fully automated and performs iterative cycles of labeling, imaging, and removing spectrally distinct fluorophores until all the biomarkers have been imaged using a standard fluorescence microscope. The images are then collected and compiled across all the imaging cycles to achieve single-cell resolution for all the markers. The single-step staining and gentle fluorophore removal not only allow for highly multiplexed biomarker analysis but also preserve the sample for additional downstream analysis if desired (e.g., hematoxylin and eosin staining). Furthermore, the image analysis software enables image processing-drift compensation, background subtraction, cell segmentation, and clustering-as well as the visualization and analysis of the images and cell phenotypes for the generation of spatial network maps. In summary, this technology employs a computerized microfluidics system and fluorescence microscope to iteratively hybridize, image, and strip fluorescently labeled DNA probes that are complementary to tissue-bound, oligonucleotide-conjugated antibodies.

Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image&#160;analysis technique.

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is ...

癌症研究

肿瘤微环境的多重免疫荧光和空间图像分析

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.
We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.
This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

作者聚焦：多重免疫荧光结合空间图像分析用于肿瘤微环境的临床和生物学评估  

In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending ...

绘制肿瘤免疫景观图谱：深入的多重 IHC 分析方案

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

作者聚焦：解锁对肿瘤免疫细胞景观的见解

This protocol describes in detail how immune cell characterization of the tumor microenvironment using multiplex immunohistochemistry is carried out.

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. ...

Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell interaction known as the immunological synapse. F-actin is also speculated to play a role in regulating molecular distributions at the membrane of cells including sub-membranous vesicle dynamics and protein clustering. While standard light microscope techniques allow generalized and diffraction-limited observations to be made, many cellular and molecular events including clustering and molecular flow occur in populations at length-scales far below the resolving power of standard light microscopy. By combining total internal reflection fluorescence with the super resolution imaging method structured illumination microscopy, the two-dimensional molecular flow of F-actin at the immune synapse of T cells was recorded. Spatio-temporal image correlation spectroscopy (STICS) was then applied, which generates quantifiable results in the form of velocity histograms and vector maps representing flow directionality and magnitude. This protocol describes the combination of super-resolution imaging and STICS techniques to generate flow vectors at sub-diffraction levels of detail. This technique was used to confirm an actin flow that is symmetrically retrograde and centripetal throughout the periphery of T cells upon synapse formation.

To investigate flow velocities and directionality of filamentous-actin at the T cell immunological synapse, live-cell super-resolution imaging is combined with total internal reflection fluorescence and quantified with spatio-temporal image correlation spectroscopy.

使用madSTORM进行高分辨率，超分辨率的T细胞成像

摘要

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此视频中的章节

一个实时，同步成像的TCR和其相关的信号转导蛋白的TIRF显微镜技术

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

皮层肌动蛋白流通过结构照明显微镜数据的时空图像相关光谱量化性T细胞

使用madSTORM进行高分辨率，超分辨率的T细胞成像

摘要

探索更多视频

此视频中的章节

一个实时，同步成像的TCR和其相关的信号转导蛋白的T​​IRF显微镜技术

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

肿瘤微环境空间免疫细胞景观的多重免疫组织化学分析

皮层肌动蛋白流通过结构照明显微镜数据的时空图像相关光谱量化性T细胞

一个实时，同步成像的TCR和其相关的信号转导蛋白的TIRF显微镜技术