Name: molecular diffusion in plasma membranes of primary lymphocytes measured by fluorescence correlation spectroscopy
Uploaded: 2017-02-01T12:30:00.000+00:00
Duration: 12 min 6 s
Description: Watch this Scientific Journal Video about Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy at JoVE.com

我们感谢Vladana武克杰维奇博士，分子医学中心，卡罗林斯卡学院对维护蔡司Confocor 3仪器，并为有关小区测量有用的技巧。这项研究是由来自Vetenskapsrådet资助（批准号2012- 1629），马格努斯Bergvalls stiftelse，并从Stiftelsen克拉斯Groschinskys minnesfond资助。

1.染色的FCS <ol><li>隔离用磁珠标记，按照生产商的方案16脾淋巴细胞的小鼠NK细胞。使用每个样品2-3×10 5个细胞用于以下的步骤。 注意:使用阴性选择，以丰富的靶细胞群体，留下不变，从而使细胞可以单独使用初级抗体进行标记。请参阅从小鼠2细胞分离更详细的信息参考2。 </li><li>用于表达Fc受体鼠细胞，阻断Fc受体与抗体克隆2.4G2在25微升磷酸盐缓冲盐水（PBS）和每个样品的1％胎牛血清（FBS）的5微克/微升。孵育在室温下15分钟。 </li><li> 抗体的制备将。 <ol><li>使用的抗体直接偶联于光稳定荧光团。如果对两种不同蛋白的两种抗体是具有良好的分离的发射光谱，以尽量减少串扰（ 例如，通过在488和633的激光器2激励时，在后面的协议分别称为"绿色"和"红色"的激光器和荧光团，使用时，使用的荧光团）。 注:如果标记光稳定的荧光团的商业抗体无法提供所选择的生物标志物，以荧光团偶联物的未标记的抗体根据制造商的说明。见材料表用于本研究中使用的抗体。 </li><li>通过稀释针对该蛋白或在PBS + 1％FBS的目的蛋白质的荧光标记的抗体制备抗体混合物。该抗体组合，以每个样品添加到每个样品50μl的终体积。冰上孵育在黑暗中45分钟。 注:优化的抗体的浓度预先以确保该抗体以饱和浓度使用时，典型地1-10微克/毫升。 </li></ol></li><li>温育后，通过加入250微升的PBS洗涤细胞，并在150 xg离心离心他们3分钟。弃去上清液。 </li><li>重复步骤1.4。 </li><li>悬浮细胞在200微升PBS + 1％FBS的。保持在冰上，并在黑暗中直到采集。 注:小鼠NK细胞可保持在冰上达10小时。 </li></ol> 2.显微镜腔室盖玻片幻灯片的制备注意:使用腔玻璃罩幻灯片或菜肴与盖玻璃厚度，该显微镜已经优化，无论是＃1或＃1.5。如果显微镜是不为一定的厚度对齐，或者如果它是未知的，在显微镜环圈需要为当前玻璃罩厚度17进行优化。 <ol><li>稀聚L-赖氨酸用蒸馏水在一个1:10的比例。加入200μl稀释聚L-赖氨酸的腔室，并培育20分钟。 </li><li>去除聚L-赖氨酸通过抽吸并通过在室温下放置它没有盖子为至少20-30分钟让该室的空气干燥。 </li></ol> 3.启动FCS系统注意:此协议是指一个特定的显微镜系统和软件（参见材料/试剂表 ），虽然其它显微镜设置和软件包也可以使用。 <ol><li>打开与FCS的相关器的共聚焦激光扫描显微镜。打开"专家模式"的软件。选择40X水浸泡镜头。 </li><li>在"获取"选项卡上，按"配置"和"扫描"按钮，打开"配置控制"和"扫描控制"窗口（ 图1窗口A和B，分别）。在"Confocor"选项卡，按"办法"，打开"测量"窗口（ 图1窗口C）。 </li><li>创建一个文件夹来保存FCS测量。通过单击"文件"选项卡下的"新建"开始一个新的图像数据库。 </li><li>使用"激光"按钮，打开卤素灯和用于激发荧光团的有关激光器（例如，对于"绿色"激发激光器和633nm的激发为"红"激发激光器488纳米）。 </li><li> 选择合适的激发和发射滤波器和激活相应的检测器。 <ol><li>为图像捕获指定的设置，包括激发激光，激发和发射滤波器，光路，以及检测器所用，在"配置控制"的窗口。 </li><li>同样，在"测量"窗口中指定的FCS测量相应的设置，在"系统配置"选项卡下。使用类似的设置尽可能为成像和FCS。 </li><li>通过检查"CH1"框为绿色激活信道均衡为FCS录音检测通道升和"CH2"在"测量"窗口红色通道。 注:设置应为所用的荧光团（多个）进行优化，如在一个标准共焦成像实验。在随后的实验中，相同的FCS设置可以通过打开一个旧的FCS文件，使用"Confocor"下拉菜单在用户界面的顶部，并选择可重复使用的"打开文件"。在新兴的采集窗口，按"回用"。同样，图像采集设置，可以通过打开保存的图像，然后按加载"重用"。 </li></ol></li><li>等到激光是进行FCS测量前保持稳定。这可能需要长达气体激光器30分钟，而二极管激光器稳定较快。调整针孔一边等待。 </li></ol> 4.针孔调整<ol><li>制备相应于抗体标签的激发和发射光谱的荧光团或荧光染料的0.2-0.5微米的解决方案。该荧光一定知道扩散系数18，19。 </li><li>把溶液50微升下降与绿色激光的井在墓室玻璃罩幻灯片中心激发的荧光。放的蒸馏水对40X水客观一滴和滑动定位。按"可见"按钮，开始可见光和使用眼部找到并专注于荧光下降。 注:使用同一张幻灯片作为以后小区测量，因为玻璃厚度假定细微变化之间的幻灯片会影响显微镜对齐。 </li><li>将焦点置于井内的液滴（10-100微米从底部）。 </li><li>在"测量"窗口中，选择"采集"选项卡。按"当前位置"下的"位置"（ 图1窗口C）。 </li><li>返回到"系统配置"选项卡在同一个窗口。设置高磷奥尔为绿色激光。 注:高的激光功率是指饱和功率（ 即，荧光信号不呈线性如果激光功率进一步增加时增加）。大约1系统毫瓦的功率设置，或最大激光功率的5％-10％，通常是不够的。 </li><li>按测试信号的稳定性"开始"。这将打开一个显示当前测量时间跟踪和自相关曲线一个单独的窗口。检查的荧光信号随时间是高的，稳定的，并且在kHz而非赫兹范围示出的波动。 </li><li>在"测量"窗口中选择"澳调节"按钮。检查，如果选择了合适的检测信道（CH1或CH2）。按"其中autoAdjust X."如果得到的曲线没有一个明确的最高展示，或最大是在边缘，再选中"粗"选项，按"其中autoAdjust X"。当在x方向上产生的屏幕结束时，执行SA我要Ÿ按"其中autoAdjust Y"。 </li><li>按"其中autoAdjust"，直到都有明确的最大值和值没有测量之间的变化去调整选择X和Y之间"粗"和替代。 </li><li>如果细胞被标记有两种不同的荧光团，移动到红色荧光团溶液已加入的腔室。选择红色激光高激光功率和重复的红色激发和检测通道步骤4.6-4.8。 注意:如果X和Y值，其中只有一个针孔同时用于检测通道的系统通道之间的偏离，选择中间值，然后按OK接受更改。这里，对于488纳米激光在X = 79且Y = 189最大值和633-nm激光器最大值在X = 80且Y = 188，值X = 80且Y = 189被选定。在488纳米和633纳米激光器标记由488纳米或633纳米激发的荧光团的两种抗体的激发的组合是一个很好的选择，因为如果发射光谱不重叠2串扰风险被最小化。 </li></ol> 5.测量荧光基团自由的在途时间注意:通过通过与公知的扩散系数荧光团的焦点（TAUD）确定所述传播时间，检测体积的大小，因此，细胞膜是焦点内的面积，可以计算出来。 TAUD的计算在步骤7.2中描述。 <ol><li>使用用于针孔调整相同的解决方案，在"测量"窗口（ 图1，窗口C）设置采集时间为30秒×2的重复「收购」选项卡下。 </li><li> 通过在"测量"窗口（图1，窗口B）点击"开始"开始测量。 <ol><li>进行，每一激励激光和在溶液中的相应的荧光，激光功率系列开始处或附近饱和功率和由半每个测量下降。在"测量"窗口（ 图1，窗口C）的"系统配置"选项卡中更改激光功率。按"开始"按钮，开始测量。 注:包括在较低的范围即将小区测量的激光功率（ 例如，测量在16，8,4，和2μW功耗，目标前）20。系统的激光设置在比输出激励一般较高，可以变化在很大程度上依赖于显微镜和对准的质量。在这个系统中，上面功率范围对应于大约60-500的μW系统设置功率。它建议使用功率计的目标之前，以测量功率输出第一次使用新的显微镜。激光器的电流最大功率下的"测量"的窗口的"信息"按钮找到。 </li><li>写下每摩尔的计数隶:从每个激光功率测量（CPM，单位千赫）。 </li><li>如果使用两个检测通道，检查显示为串扰的自相关曲线的窗口。使用仅含有绿色荧光来测量红色检测信道检测到的FCS自相关，并与仅红色荧光团中的溶液，以评估在绿色检测通道检测的溶液中。作为一个经验法则，不断从下面的特定信号的5％的"错误"的荧光从正确的荧光检测的CPM。 </li><li>检查值所使用的激光功率线性扩展。在最高的激光功率CPM的饱和度（ 即略低值比的线性关系预期）是可以接受的。 注:CPM应远高于10的最高激光功率对于几乎所有显微镜系统和普通的荧光团，并且可以是对敏感系统显著更高。第一次使用新的共轭荧光抗体，执行抗体的FCS测定自由扩散在溶液量化预期CPM。在测量之前，涂层测量室用200μl聚-L-赖氨酸与聚乙二醇（稀释至0.5毫克在PBS / ml）在室温下1小时接枝。用吸管除去液体，并允许该腔室在空气中干燥。保存在冰箱中储液（最多2周）和粉末库存在冷冻。在显微镜下，稀释抗体在PBS 1-10微克/毫升。按照步骤4.2-4.4，并在该协议6.7。如果表面没有涂有不粘溶液，抗体将与玻璃表面相互作用并迅速地从溶液中耗尽。 </li></ol></li></ol> 6.电池测量<ol><li>从抗体标记的细胞悬浮液（步骤1.5）和150微升透明罗斯韦尔园区纪念研究所介质1640（RPMI）的成8孔腔玻璃罩幻灯片的一个孔在PBS + 1％FCS中添加125微升的细胞。乐开始FCS测量前AVE在黑暗中的细胞以测定温度为至少20分钟。 注意:这是允许细胞沉降并附着到孔的底部，并与细胞和溶液平衡至测定温度。 </li><li>在"扫描控制"窗口（ 图1，窗口B），设置缩放1，按"快速XY"按钮开始快速扫描XY。修改激光功率，使得当细胞仍清晰可见它是尽可能低。围绕平均亮度，其中该膜被明确界定并且在细胞质无荧光信号的圆形细胞的图像。放大到小区覆盖了大部分的图像。 </li><li>如果当前单元格是移动或显示卷须，型材，或极度亮点选择一个新的单元格。为保持相同的实验过程中捕获的所有细胞相同的变焦和激光功率。 注:竖起膜也可以是即将到来的APO的标志下垂。 </li><li>着眼于细胞膜的顶部。在"测量"窗口（ 图1，窗口C）的"收购"选项卡中，通过激活选择FCS测量的位置"十字线"。或者，选择"LSM图像"选项卡，选中LSM图像中的要测量点，按"添加位置"。 注:细胞膜的顶部不会被非特异性结合到聚-L-赖氨酸的荧光抗体或荧光团的影响。然而，以确定该小区没有在测量过程中移动（见结果）是重要的。 </li><li>在"测量"窗口（ 图1，窗口C）的"收购"选项卡，设置重复次数为6-10，用"测量时间"设定在每个重复10秒。 </li><li>返回到"测量"窗口的"系统配置"选项卡。调整为FCS测量激光功率下的"LASER"按钮。目标之前，使用低功率小区测量，在1和10微瓦20之间的范围内。 注:推荐值是信号检测和光损伤在细胞间的权衡。见步骤5.2.1注激光功率的这些值对应于百分比。 </li><li>通过在"测量"窗口（窗口C）按"启动"启动FCS测量。如果小区漂白显著在测量开始时，由30％以上的强度跟踪下降的前10秒期间（一个例子示于图3A，下图）所检测，移动到另一个小区和低激光功率为未来的测量。 <ol><li>如果信号丢失，调整在Z方向上的焦点。测量完成后，使用"扫描控制"的窗口（ 图1，窗口B）中，以检查细胞仍然居中并且测定细胞膜。如果日Ë细胞已经转移，放弃测量。 </li><li>在显示测量的自相关窗口中，手动删除包含缩放演习，漂白，大型集群，或其他文物（ 见图3的例子）个体重复。通过标记，单击鼠标右键，并选择这样做"删除"。保存.fcs格式的最终​​文件。减每单元至少4个重复。 </li></ol></li><li>任选地，使用"扫描控制"窗口获得的中间部分（与膜可见的整个圆周）的细胞的图像。捕捉图像的FCS的测量后，以避免漂白。按"单"按钮开始捕获图像。 </li><li>如果使用"添加位置"为重点FCS定位，点击移动到下一个单元格之前"删除位置"。 </li><li>改变到细胞悬浮液的新等分试样的最大测量的2小时后，以保持细胞的存活throughout为实验。 </li></ol> 7. FCS分析<ol><li>打开.fcs文件与曲线拟合功能的软件（见材料/试剂表在本协议中所使用的软件）。 注:自带的显微镜FCS软件是一个好地方，熟悉基本的装修，但额外的软件是必要的，以适应两维膜扩散。 </li><li>首先，通过分析游离荧光团测量确定的激发体积的大小。适合的3维自由扩散曲线的自相关的曲线21。 <img alt="方程" src="/files/ftp_upload/54756/54756eq1.jpg" /> （式1） 注意:参数定义:N:指的是在聚焦体积，τ（头）的荧光实体数量:相关时间τD（TAUD）:在聚焦体积的平均停留时间，T 1:概率为荧光团是在三重态，τ&lt;子&gt; T:弛豫时间为单线三重态跃迁，S:高宽比为直径的焦点量。 <ol><li>提取TAUD，运输时间为分子转移焦点。 </li><li>使用用于校准18,19荧光团的观察TAUD出版扩散系数（D）的计算针孔半径（ω）。 <img alt="方程" src="/files/ftp_upload/54756/54756eq2.jpg" /> （式2） </li></ol></li><li> 分析细胞膜上的自相关曲线。 <ol><li>为了显现表示分子扩散曲线的一部分，选择开始自相关曲线的最陡的斜率之前和1的曲线收敛后结束的时间框架（ 例如，0.001〜5秒，鼠表面受体;参见图4）。 </li><li>生成保存我的个体重复的平均自相关曲线n阶6.7.2。 </li><li>适合2维膜扩散曲线的每个均使用等式3 3的自相关曲线。 <img alt="方程" src="/files/ftp_upload/54756/54756eq3.jpg" /> （式3） 注:重要输出参数如下:N是驻留在兴奋膜面积内分子的平均数目。重新计算密度（N /微米2）。 τD（TAUD）:在焦点区域的平均停留时间，由膜（S）的两维限制。重新计算的平均停留时间，以通过所确定的针孔半径（ω），等式2的T1的扩散系数（微米2 /秒）为荧光团是在三重态的概率。亮度（CPM）通过由N除以测量的平均总强度计算</li><li>如果般配不是在第一次尝试实现，改变它的开始值和/或所述上限和下限为变量直至THIs被获得。 注:在小学细胞膜蛋白扩散速率典型的上层下限10-500毫秒TAUD，为T1 0-100％，和0.1-5毫秒TauT1。选择在这些间隔的中间开始的嵌合值。表示从扩散衍生通常位于1毫秒和1秒之间的荧光的波动曲线的一部分（参见图4）。根据不同的荧光团，存在有时会第二工艺目前，在更短的时间尺度比扩散参数引起自相关。这是通过一过暗状态（三重峰）或闪烁引起的（如经常发生荧光蛋白）。三重态是占在等式3中，并且在这些情况下所呈现的模式应该因此也提供了良好的配合。 </li></ol></li></ol>

<ol>
	<li>Goni, F. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+basic+structure+and+dynamics+of+cell+membranes:+an+update+of+the+Singer-Nicolson+model.">The basic structure and dynamics of cell membranes: an update of the Singer-Nicolson model.</a> Biochim Biophys Acta. 1838, 1467-1476 (2014).</li><li>Bagawath-Singh, S., 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=Cytokines+Induce+Faster+Membrane+Diffusion+of+MHC+Class+I+and+the+Ly49A+Receptor+in+a+Subpopulation+of+Natural+Killer+Cells.">Cytokines Induce Faster Membrane Diffusion of MHC Class I and the Ly49A Receptor in a Subpopulation of Natural Killer Cells.</a> Front Immunol. 7, (2016).</li><li>Garcia-Saez, A. J., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+correlation+spectroscopy+for+the+study+of+membrane+dynamics+and+protein/lipid+interactions.">Fluorescence correlation spectroscopy for the study of membrane dynamics and protein/lipid interactions.</a> Methods. 46, 116-122 (2008).</li><li>Machan, R., Wohland, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+applications+of+fluorescence+correlation+spectroscopy+in+live+systems.">Recent applications of fluorescence correlation spectroscopy in live systems.</a> FEBS Lett. 588, 3571-3584 (2014).</li><li>Mutze, J., Ohrt, T., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+correlation+spectroscopy+in+vivo.">Fluorescence correlation spectroscopy in vivo.</a> Laser Photon Rev. 5, 52-67 (2011).</li><li>Lidke, D. S., Wilson, B. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Caught+in+the+act:+quantifying+protein+behaviour+in+living+cells.">Caught in the act: quantifying protein behaviour in living cells.</a> Trends Cell Biol. 19, 566-574 (2009).</li><li>Manzo, C., Garcia-Parajo, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+review+of+progress+in+single+particle+tracking:+from+methods+to+biophysical+insights.">A review of progress in single particle tracking: from methods to biophysical insights.</a> Rep Prog Phys. 78, 124601 (2015).</li><li>Wiseman, P. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+correlation+spectroscopy:+principles+and+applications.">Image correlation spectroscopy: principles and applications.</a> Cold Spring Harb Protoc. , 336-348 (2015).</li><li>Sankaran, J., Shi, X., Ho, L. Y., Stelzer, E. H., Wohland, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ImFCS:+a+software+for+imaging+FCS+data+analysis+and+visualization.">ImFCS: a software for imaging FCS data analysis and visualization.</a> Opt Express. 18, 25468-25481 (2010).</li><li>Liu, P., Ahmed, S., Wohland, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+F-techniques:+advances+in+receptor+protein+studies.">The F-techniques: advances in receptor protein studies.</a> Trends Endocrinol Metab. 19, 181-190 (2008).</li><li>Manley, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-density+mapping+of+single-molecule+trajectories+with+photoactivated+localization+microscopy.">High-density mapping of single-molecule trajectories with photoactivated localization microscopy.</a> Nat Methods. 5, 155-157 (2008).</li><li>Bacia, K., Haustein, E., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+correlation+spectroscopy:+principles+and+applications.">Fluorescence correlation spectroscopy: principles and applications.</a> Cold Spring Harb Protoc. , 709-725 (2014).</li><li>Haustein, E., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+correlation+spectroscopy:+novel+variations+of+an+established+technique.">Fluorescence correlation spectroscopy: novel variations of an established technique.</a> Annu Rev Biophys Biomol Struct. 36, 151-169 (2007).</li><li>Widengren, J., Thyberg, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FCS+cell+surface+measurements--photophysical+limitations+and+consequences+on+molecular+ensembles+with+heterogenic+mobilities.">FCS cell surface measurements--photophysical limitations and consequences on molecular ensembles with heterogenic mobilities.</a> Cytometry A. 68, 101-112 (2005).</li><li>North, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seeing+is+believing?+A+beginners'+guide+to+practical+pitfalls+in+image+acquisition.">Seeing is believing? A beginners' guide to practical pitfalls in image acquisition.</a> J Cell Biol. 172, 9-18 (2006).</li><li>Meinhardt, 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=Influence+of+NK+cell+magnetic+bead+isolation+methods+on+phenotype+and+function+of+murine+NK+cells.">Influence of NK cell magnetic bead isolation methods on phenotype and function of murine NK cells.</a> J Immunol Methods. 378, 1-10 (2012).</li><li>Bacia, K., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Practical+guidelines+for+dual-color+fluorescence+cross-correlation+spectroscopy.">Practical guidelines for dual-color fluorescence cross-correlation spectroscopy.</a> Nat Protoc. 2, 2842-2856 (2007).</li><li>Gendron, P. O., Avaltroni, F., Wilkinson, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+coefficients+of+several+rhodamine+derivatives+as+determined+by+pulsed+field+gradient-nuclear+magnetic+resonance+and+fluorescence+correlation+spectroscopy.">Diffusion coefficients of several rhodamine derivatives as determined by pulsed field gradient-nuclear magnetic resonance and fluorescence correlation spectroscopy.</a> J Fluoresc. 18, 1093-1101 (2008).</li><li>Petrasek, Z., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precise+measurement+of+diffusion+coefficients+using+scanning+fluorescence+correlation+spectroscopy.">Precise measurement of diffusion coefficients using scanning fluorescence correlation spectroscopy.</a> Biophys J. 94, 1437-1448 (2008).</li><li>Stromqvist, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+modified+FCCS+procedure+applied+to+Ly49A-MHC+class+I+cis-interaction+studies+in+cell+membranes.">A modified FCCS procedure applied to Ly49A-MHC class I cis-interaction studies in cell membranes.</a> Biophys J. 101, 1257-1269 (2011).</li><li>Widengren, J., Mets, U., Rigler, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+Correlation+Spectroscopy+of+Triplet-States+in+Solution+-+a+Theoretical+and+Experimental-Study.">Fluorescence Correlation Spectroscopy of Triplet-States in Solution - a Theoretical and Experimental-Study.</a> J Phys Chem. 99, 13368-13379 (1995).</li><li>Humpolickova, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Probing+diffusion+laws+within+cellular+membranes+by+Z-scan+fluorescence+correlation+spectroscopy.">Probing diffusion laws within cellular membranes by Z-scan fluorescence correlation spectroscopy.</a> Biophys J. 91, L23-L25 (2006).</li><li>Guo, S. 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=Bayesian+approach+to+the+analysis+of+fluorescence+correlation+spectroscopy+data+II:+application+to+simulated+and+in+vitro+data.">Bayesian approach to the analysis of fluorescence correlation spectroscopy data II: application to simulated and in vitro data.</a> Anal Chem. 84, 3880-3888 (2012).</li><li>Ries, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+suppression+of+sample-related+artifacts+in+Fluorescence+Correlation+Spectroscopy.">Automated suppression of sample-related artifacts in Fluorescence Correlation Spectroscopy.</a> Opt Express. 18, 11073-11082 (2010).</li><li>Chiu, C. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intracellular+kinetics+of+the+androgen+receptor+shown+by+multimodal+Image+Correlation+Spectroscopy+(mICS).">Intracellular kinetics of the androgen receptor shown by multimodal Image Correlation Spectroscopy (mICS).</a> Sci Rep. 6, 22435 (2016).</li><li>Wegel, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+cellular+structures+in+super-resolution+with+SIM,+STED+and+Localisation+Microscopy:+A+practical+comparison.">Imaging cellular structures in super-resolution with SIM, STED and Localisation Microscopy: A practical comparison.</a> Sci Rep. 6, 27290 (2016).</li></ol>

The authors have nothing to disclose.

这个协议的FCS可用于表面分子上的所有类型的免疫细胞（鼠的，人的，或其他物种）的分子动力学的评估。 FCS措施时空分子动力学下降到活细胞中的单分子的分辨率。分子密度，以及感兴趣的蛋白质的扩散速度和集群动力学，可以从自相关曲线中提取。 荧光标记是成功的FCS实验枢轴重要性。的细胞膜上的感兴趣的蛋白质传统上一直使用抗体标记和抗体常常最方便对幼稚免疫细胞表面蛋白的使用。未标记的抗体必须直接缀合到光稳定的荧光染料具有高分子亮度。所述荧光团为抗体缀合的选择是用于测量的质量很重要。标准标签流式细胞仪，如荧光素和基于藻红蛋白染料，不推荐由于快速漂白。光稳定染料直接缀合到抗体目前由几家公司提供。的制造商通常提供用于缀合，将所得的共轭抗体的纯化令人满意的协议，这可以在几个小时内完成。另外，也可以使用荧光蛋白来执行FCS，但特别应注意，以尽量减少激光功率，因为​​荧光蛋白是一般更容易漂白比最光稳定的化学荧光。根据以前的经验，过度表达的蛋白质通常会导致在扩散率由于拥挤大幅下降，这使得使用荧光蛋白的不合适。 之前的测量针孔校准也是一个关键步骤。用于确定聚焦体积的大小的荧光团必须知道扩散系数秒（见等式2）。用密切对应于抗体标签的发射光谱自由荧光团，以确定聚焦体积的大小。这一操作必须完成，以保证最佳的信号效率和颜色通道之间潜在的交叉相关的正确检测。执行FCS的激光功率系列的自由扩散性荧光团，以确保系统给出的范围内的权力的预期输出信号。在实验之间的相同的激光功率比较CPM，以确保实验之间的一致性。 在分析步骤，它是必不可少的拟合模型时把合理的范围和初始值的变量。使用相似的电池系统此前公布的知识找到好的起点。从理论上讲，FCS是一个定量的技术，但由于最佳条件很少发生，有一定程度的谨慎有解释结果时才能作出。所有类型的波动将被记录，不管这种波动的来源。因此，它是有关于实验系统尽可能多的信息可能以排除可能的误差源是有用的。例如，全细胞膜的运动将产生与较长TAUD（ 图3A）的波动，而在溶液中的游离荧光团的推定污染物会具有至少十倍较短TAUD扩散。 这个基本协议可以以多种方式进行修改。如果两种蛋白质都标有不同的荧光团，共扩散（相互作用的间接测量）可以通过扩展的方法来检测互相关进行评估。到这些蛋白质结合在细胞膜上彼此的程度由相对于各个颜色信道的自相关曲线的高度互相关曲线的高度表示。互相关是在测量软件表示为CH1-CH 2。预交叉相关的CISE分析需要串扰控制和因此比这里介绍的协议较为复杂。如何着手，作为一个扩展这一基本协议的详细描述，可以在Strömqvist 等人发现。 13。为了优化在z方向上的定位，z轴扫描的FCS可以使用22。根据以往的经验，这是令人满意的手动执行此操作。另外，也可以以适合多个扩散系数至FCS自相关曲线23。这需要具有不同的扩散率和亚群中的至少一个的近似扩散速率的亚群数量的以前的知识。否则，将有过多的自由变量，这将呈现的嵌合不可靠的。一个典型的例子是一个表面蛋白，其扩散速度大大放缓了结合的配体。最后，cleani纳克离群的痕迹，而不完全去除重复是可能24。 缺乏荧光信号是解决一个共同的问题。用于自由地扩散荧光团，可以使用卤灯，以检查是否降是荧光的。如果降不荧光，混合了一批新的荧光带略有增加浓度（nM范围内），然后再试一次。检查焦点荧光滴内，则激光器在软件接通时，激光功率是足够的，正确的发射滤波器和检测器被选择，而在"FCS测量"窗口的右信道被激活时（见步骤3.6）。启动激光器并从侧面看在视觉上确认该激光光到达样品。避免直视激光源。如果所选发射滤波器包括激光波长，快门自动阻挡光路，以避免检测器的损坏。一世女不限的设置都不错，但没有光到达后，重新启动激光器，FCS系统，和计算机。询问专家，如果缺乏荧光信号的存在。简化程序适用，如果标记的细胞不显示荧光。确认卤素灯荧光的存在;开启激光器，选择激光器通道，并调整激光功率。选择在细胞膜上的位置时，无论是使用"十字线"或"添加位置"选项（见步骤6.4）。切换到下一个样品，如果该信号仍然太低。 该技术的波动的基础的一个重要方面是，分子必须是合理的移动被检测到。非常缓慢地移动分子或在整个测量时间被困比焦点更小的区域内的分子级分，因此不能测定。这导致表面密度的可能低估和扩散速度的过高估计。漂也可以向密度和TAUD两者的推定低估，因为分子将具有被漂白它们在激光照射聚焦体积花费较长时间的较高概率。从背景（从焦平面之外荧光）的影响会，另一方面，人为地增加检测分子的数量和减少所测得的CPM。以前，在绝对密度测定总最大误差估计为大约40％20。然而，它通常是可能的不同的生物样品进行比较，以彼此，由于误差来源是，在大多数情况下，在整个实验相等。另一个潜在的误差来源是抗体是二价的，这意味着每个抗体可以潜在地结合到两个目标分子。作者没有观察这种现象，但它不能保证，这是对于其他抗体的全局特征。二价的潜在影响，必须因此，为每个抗体的单独测试。具体的初级和次级标记抗体的组合绝不能使用，因为从两个连续的二价标签诱导人工集群的高风险。如果细胞已代替被转用感兴趣的蛋白质的荧光蛋白标记的版本中，每个蛋白将只有一个标签。然而，这需要染，这并不总是理想的，甚至可能没有可能（ 例如，如果使用的免疫细胞从人血液直接分离）。最后，单点FCS不录制图像。如果需要供出版或其他目的的图像，这些必须单独使用软件的摄像部拍摄的。总是捕获FCS的测量后的图像，以避免在细胞表面的不必要的漂白。 FCS不同，传统的基于共聚焦显微镜，如FRAP和图像相关方法不能量化荧光波动在单分子水平6。图像相关方法测量分子数间接与较低的分辨率，但它们可以评估在整个成像区域25分子扩散和集群的可变性。通过共聚焦显微镜测量标准SPT具有标签的理想水平，要比FCS 7低几个数量级。因此，标记的蛋白质的密度不能用标准的SPT测定。 SPT与其他显微镜技术的组合（ 例如，随机光学重构显微术或光活化定位显微镜）允许的密度和运动进行评估，但它需要非常专业化的染料或蛋白11。超分辨率技术，如结构照明显微镜和受激发射耗尽显微术，通常需要固定的样品与初级的组合和用于labelin二级抗体摹26。因此定位是非常精确的，而该系统的动力学常常不能进行评估。相比于SPT和超分辨率技术，FCS还需要用于分析和结果提取显著较少的计算机的功率和时间。流式细胞术是免疫学的主力，可与FCS的有利地结合起来。细胞分选可以，例如，随后通过在选定的细胞群的后续测量，如果光稳定染料之前已排序使用。 FCS因此，可单独使用或与其它已建立的方法中使用的方法。 该协议可以用于在单分子水平在细胞膜内，以确定免疫细胞动力学和相互作用的目前未知的功能。此外，全人群与选择的子集的功能可以比拟的。它也有作为用于免疫细胞疗法的选择步骤中的潜在作用。由于测量做不消耗电池，不同于大多数其他方法用于研究免疫细胞的功能，单个细胞可以潜在地回收并培养。因此，FCS曲线的分析之后，有前途的细胞可以提取更多的应用，包括公认的临床应用扩展。

许多免疫细胞的功能依赖于分子扩散和薄膜内的相互作用。生物膜是复杂的，许多因素可能对免疫细胞的功能，可以细胞膜1内影响蛋白的平移扩散的速度很重要。我们最近发现，属于先天性免疫系统天然杀伤（NK）细胞，淋巴细胞，在细胞膜呈现2研究蛋白质的差扩散取决于NK细胞活化2的状态。 荧光相关光谱（FCS）是一种技术，其能够生物膜内量化分子扩散率。它报告的平均扩散速度的荧光标记的分子在一个固定的体积，共焦显微镜的通常的焦点。它是基于波动的荧光时在分子的运动所发生的测量在稳定状态下的系统。 FCS已广泛用于研究荧光染料和蛋白质的扩散，无论是在溶液和脂质膜之内。影响扩散速率其他输出参数也可以用这种方式来间接地研究（ 例如，蛋白质或细胞膜上的分子相互作用的构象变化）3，4。 FCS的突出相比，由于其高灵敏度的其他技术，允许单分子检测的可能性。它可以很好地用于分子浓度在纳摩尔到毫摩尔范围内，这是典型的大多数蛋白质5的内源表达水平。另外，FCS可以给所研究的容积内的蛋白质的绝对数量的近似，而大多数其它技术仅得到约蛋白质表达水平的相对信息。其他的方法来测量分子扩散率中膜包括FLUO漂白（FRAP）后rescence恢复，单粒子跟踪（SPT），多个针孔FCS和图像相关方法。 FRAP和图像相关方法集合技术，其通常不提供有关分子10的绝对数量的信息。相对于SPT，FCS的吞吐量是关于表征人口平均水平。由于激光焦点中存在的分子的平均扩散速度被测量，而不是单分子速度的分析也是要求不高。此外，除非专门显微镜可用11，SPT不能给关于浓度的任何信息，因为标准的SPT标签必须非常低，以允许单个分子的鉴定。另一方面，FCS要求所研究的分子是移动的。它根本不会发现任何假定不动的分数或分子移动的速度很慢。分子的扩散速率居住超过约十分之一的采集时间不会FCS测量3，12代表正确的时间越长，内对焦。因此，通过FCS记录扩散系数往往比从像FRAP和SPT，其中接近对不动和非常慢的部分都考虑在内，以及技术报告的扩散速率快。 SPT也会给分子群体比FCS将内扩散速率的可变性的一个更详细的说明。 FCS的量化的荧光强度随时间的兴奋体积内的波动。在膜的测量的情况下，这转化为在膜的照明面积。在本文中，我们利用的事实，这样的波动是由表现出布朗扩散分子诱导和中和了的激发体积因而移动。也有用于fluctua几个其它可能的来源系统蒸发散在荧光信号，如闪烁的或三重态的荧光团，环境效应的存在，结合-解除绑定的配位体，或整个细胞膜的运动。这些推定的误差源需要以准确解释结果12,13设计一个FCS的实验时，必须考虑到。通常，在生物膜的横向扩散速率是由于拥挤和相互作用低，两膜蛋白之间和蛋白质和细胞骨架之间。从历史上看，在膜中使用的FCS就此受到阻碍缺乏光稳定的荧光团，它被要求，以避免在通过激励焦点14延长运输时间漂白。然而，今天，有很多合适的光稳定的染料选择。在探测器和其他硬件显著的改进也让荧光prote检测插件和低亮度的染料。这里，对于FCS的使用鼠初级淋巴细胞中的应用，其中，感兴趣的蛋白质标记有荧光标记的抗体的基本协议，进行说明。适合以提取扩散系数和分子密度的自相关曲线的方法还示出。该协议的目的是容易地随后免疫学家与技术来研究分子的扩散没有以往的经验。然而，激光共聚焦显微镜的一个基本的了解，预计（获得这一基本认识，见参考文献15）。这个协议可以相对容易地适应其他悬浮的细胞，这两种细胞系和原代细胞。有经验的FCS的用户，更精致的分析方法存在，其中一些在讨论中描述。

<table><tbody><tr><td>MACS NK Cell Isolation Kit mouse II</td><td>Miltenyi Biotec Norden&lt;sup&gt;AB&lt;/sup&gt;</td><td>130-096-892</td><td>Negative selection of NK cells</td></tr><tr><td>Fetal Bovine Serum</td><td>Sigma-Adlrich</td><td>F7524</td><td>Heat inactivated</td></tr><tr><td>Phosphate Buffered Saline</td><td>-</td><td>-</td><td>Made in house&amp;nbsp;</td></tr><tr><td>Roswell Park Memorial Institute medium 1640</td><td>PAA The Cell Culture Company&amp;nbsp;</td><td>E15-848</td><td>Transparent medium</td></tr><tr><td>Antibody clone 2.4G2</td><td>Thermo Fischer Scientific</td><td>553140</td><td>For blocking Fc-receptors.</td></tr><tr><td>Anti-Ly49A antibody&amp;nbsp;</td><td></td><td></td><td>Monoclonal antibody made in house and conjugated in house to Alexa fluor 647</td></tr><tr><td>Clone JR9.318</td><td></td><td></td><td></td></tr><tr><td>Anti-H-2Dd antibody&amp;nbsp;</td><td>BD Pharmingen</td><td>558915</td><td>Conjugated in house to MFP488</td></tr><tr><td>Clone 34.5.8S</td><td></td><td></td><td></td></tr><tr><td>MFP488</td><td>Mobiotech</td><td>MFP-A2181</td><td>Fluorescent dye for antibody conjugation.</td></tr><tr><td>Poly-L-Lysine</td><td>Sigma-Aldrich</td><td>P8920</td><td>Diluted in distilled water (1.10)</td></tr><tr><td>Poly-L-Lysine (20 kDa) grafted with polyethylene glycol (2 kDa)</td><td>SuSoS AG</td><td>PLL(20)-g[3.5]-PEG(2)</td><td>Diluted in PBS (pH 7.4) to 0.5 mg/ml.</td></tr><tr><td>Rhodamine 110 chloride</td><td>Sigma-Aldrich</td><td>432202</td><td>Known diffusion coefficient: 3.3 &amp;times; 10&lt;sup&gt;&amp;minus;10&lt;/sup&gt; m&lt;sup&gt;2&lt;/sup&gt;/sec &lt;sup&gt;19&lt;/sup&gt;</td></tr><tr><td>Alexa fluor 647</td><td>Thermo Fisher Scientific&amp;nbsp;</td><td>A20006</td><td>Known diffusion coefficient: 4.4 &amp;times; 10&lt;sup&gt;&amp;minus;10&lt;/sup&gt; m&lt;sup&gt;2&lt;/sup&gt;/sec &lt;sup&gt;20&lt;/sup&gt;</td></tr><tr><td>Confocal microscope&amp;nbsp;</td><td>Zeiss</td><td>LSM510</td><td></td></tr><tr><td>Software: Confocor 3</td><td>Zeiss</td><td></td><td></td></tr><tr><td>Software: Matlab with curve fitting toolbox</td><td>Matlab</td><td>Version R2013b</td><td></td></tr><tr><td>Nunc Lab-Tek Chambered Coverglass</td><td>Thermo-scientific&amp;nbsp;</td><td>155411</td><td>8 wells, 1.0 borosilicate bottom</td></tr></tbody></table>

molecular diffusion in plasma membranes of primary lymphocytes measured by fluorescence correlation spectroscopy

荧光相关光谱（FCS）是用于与高空间和时间分辨率研究生物膜内分子的扩散的强大技术。 FCS可以量化荧光标记的分子的分子浓度和扩散系数在细胞膜。该技术具有探索稳态免疫细胞的细胞膜分子的分子扩散特性（ 即，在不影响在实际测量时间的结果过程）的能力。 FCS是适合研究那些在典型的最内源性蛋白的水平表达的蛋白质的扩散。在此，展示了一个简单的和可靠的方法来确定主淋巴细胞细胞膜蛋白质的扩散率。以执行对抗体染色的活细胞和采集后通常发生的观测的测量的有效方法进行说明。最近进展在光稳定的荧光染料的开发可以通过缀合的感兴趣的抗体拨出不测量期间广泛漂白染料被利用。另外，这允许检测慢慢扩散实体，这是在细胞膜中表达的蛋白质的一个共同特点。该分析程序，从生成的自相关曲线中提取浓度的分子和扩散的参数被突出显示。总之，对于FCS测量一个基本协议被提供;它可以跟随免疫学家以共聚焦显微镜的理解，但是有用于测量动态参数，如分子的扩散速率的技术没有其他以往的经验。

一个典型的结果将产生在10毫秒到400毫秒膜蛋白范围内的运输时间自相关曲线。分子的数目可以为内源性表达的蛋白质0.5之间变化到每平方微米约200。仔细检查CPM高于预期不低。这可能意味着有背景信号的影响。作为一个经验法则，即接受的分析对细胞的CPM信号不应在同一激光功率自由扩散抗体是CPM低于33％。植物检疫措施应与激光功率线性扩展。用于初级免疫的细胞表面受体的自相关曲线预计是光滑，0.001和1秒之间的最陡的部分。 图2所示为具有代表性的自相关曲线和它的实时跟踪。 如在引言中简要地提及的，再有几种情况下，FCS的不适合测量分子扩散由于荧光波动其他来源，这有助于混杂的信号的影响。 图3示出了其中一个特定的细胞或测量重复应该被丢弃的情况下的例子。前面已经提到，极低的信号（非常低的CPM）被导致丢弃的单元。另一个原因丢弃个体细胞是该单元被移动（ 图3A）。在漂白的情况下（ 图3B），或者如果大型集群存在（ 图3C），如果效果是在整个测量相当或存在测量应该被丢弃。如果该功能是仅在一个或两个重复目前，这些个体重复可以被丢弃，但仍然可以使用剩余的重复。 重要的是要既使用正确的模型拟合这些数据，并且还仔细检查配合紧密的自相关曲线重叠。在图4中，显示的好的和坏的曲线拟合的例子。狠抓曲线代表扩散（最陡峭的倾斜部分）的一部分。同样重要的是，以确定这两个开始和曲线的倾斜部分的末端是公配合由模型。如果拟合是坏的，没有明显的问题，例如运动，漂白，或群集，作出最后决定丢弃小区之前修改的起始值和/或所述上限和下限（在合理的范围内）。 <img alt="图1" src="/files/ftp_upload/54756/54756fig1.jpg" /> 图1:FCS的软件接口。这里示出的是操作对FCS采集和成像软件工具所必需的主要窗口，如在该协议描述。窗口A，"配置有限公司ntrol"窗口是用于光束的路径，激光频道和用于成像滤波器控制窗口。窗口B是"扫描控制"用于成像窗口，并显示扫描设置。窗口C是"测量"的窗口，该窗口用于的FCS测量设置设置。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54756/54756fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/54756/54756fig2.jpg" /> 图2: 扩散H-2Dð 主要组织相容性类 的代表轨迹和自相关曲线 1表面新鲜分离的小鼠NK细胞的分子。在图中的上面板显示荧光波动作为时间整个7倍10秒测量的整个时间跟踪的功能。下面板代表■从这七个重复的平均自相关曲线。自相关曲线的高度成反比移动荧光标记的聚焦体积内的H-2Dð实体的浓度。在曲线的斜率最陡的部分的x轴的值，幅度的一半，表示的平均停留时间的荧光标记的H-2D的聚焦体积内ð分子。提出的测量是发表在参考文献2中的数据集的一部分。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54756/54756fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/54756/54756fig3.jpg" /> 图3: 有问题的细胞痕迹的例子 。 （A）一种运动细胞，其实例没有一个稳定的基础文件跟踪VEL。顶部面板示出了全细胞已经经过大约35秒移出焦点，如由该时间点之后的非常低的信号所表示的例子。在下部面板，其效果是更微妙的，与在几秒钟的时间间隔的起伏明显。 （B）的细胞显示漂白，跟踪随时间递减的高度。在测量开始到在测量结束比较迹线的高度。 （C）的大型集群，由在跟踪尖峰表示的存在。在上游面板，在20〜25秒一个大的集群存在。在下部面板，几个簇是整个测量本。提出的测量是发表在参考文献2中的数据集的一部分。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54756/54756fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 图 4: 曲线拟合残差和自相关代表曲线。红色和蓝色的垂直线表示用于装配的时间窗口的极限。 （A）的2维扩散模型来的样品的自相关曲线的代表配合实施例。在上游面板，绿色曲线（模型）覆盖的蓝色曲线（收购自相关），表示一个不错的选择。下面板显示从曲线拟合的残差。约1秒的波动，这是不装好，是典型的小区测量和是可以容忍的。坏配合2维扩散到相同的自相关曲线（B）的实施例。拟合模型不覆盖的自相关曲线，并且它不在1中的下面板（A和B）示出了从曲线拟合残余收敛。残差都为不良配合显著较大，特别是对于曲线的扩散部分。提出的测量是发表在参考文献2中的数据集的一部分。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54756/54756fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a>

Watch this Scientific Journal Video about Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy at JoVE.com

荧光相关光谱测量原代淋巴细胞质膜中的分子扩散- 博士论文免疫学和感染|视频

Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy

A method to measure protein diffusion in membranes of primary immune cells using fluorescence correlation spectroscopy (FCS) is described. In this paper, the use of antibodies for fluorescent labeling is illustrated.

由荧光相关光谱测量的一次淋巴细胞的细胞膜分子扩散

Fluorescence correlation spectroscopy (FCS) is a powerful technique for studying the diffusion of molecules within biological membranes with high spatial ...

molecular-diffusion-plasma-membranes-primary-lymphocytes-measured

Universidad San Sebastian

Research

Education

JoVE Journal

JoVE Core

Biology

Immunology and Infection

Cellular Processes

Membranes and Cellular Transport

SCIENTISTS IN ACTION

10.8K 次观看.  Karolinska Institutet. A method to measure protein diffusion in membranes of primary immune cells using fluorescence correlation spectroscopy (FCS) is described. In this paper, the use of antibodies for fluorescent labeling is illustrated.

视频: Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy

Methods to Assess Beta Cell Death Mediated by Cytotoxic T Lymphocytes

Type 1 diabetes (T1D) is a T cell mediated autoimmune disease. During the pathogenesis, patients become progressively more insulinopenic as 
insulin production is lost, presumably this results from the destruction of pancreatic beta cells by T cells. Understanding the mechanisms of beta cell death during 
the development of T1D will provide insights to generate an effective cure for this disease. Cell-mediated lymphocytotoxicity (CML) assays have historically used the 
radionuclide Chromium 51 (51Cr) to label target cells. These targets are then exposed to effector cells and the release of 51Cr from target 
cells is read as an indication of lymphocyte-mediated cell death. Inhibitors of cell death result in decreased release of 51Cr.
 As effector cells, we used an activated autoreactive clonal population of CD8+ Cytotoxic T lymphocytes (CTL) isolated from a mouse stock transgenic for both the alpha and beta chains of the AI4 T cell receptor (TCR). Activated AI4 T cells were co-cultured with 51Cr labeled target NIT cells for 16 hours, release of 51Cr was recorded to calculate specific lysis 
Mitochondria participate in many important physiological events, such as energy production, regulation of signaling transduction, and apoptosis. The study of beta cell mitochondrial functional changes during the development of T1D is a novel area of research. Using the mitochondrial membrane potential dye Tetramethyl Rhodamine Methyl Ester (TMRM) and confocal microscopic live cell imaging, we monitored mitochondrial membrane potential over time in the beta cell line NIT-1. For imaging studies, effector AI4 T cells were labeled with the fluorescent nuclear staining dye Picogreen. NIT-1 cells and T cells were co-cultured in chambered coverglass and mounted on the microscope stage equipped with a live cell chamber, controlled at 37&deg;C, with 5% CO2, and humidified. During these experiments images were taken of each cluster every 3 minutes for 400 minutes.
Over a course of 400 minutes, we observed the dissipation of mitochondrial membrane potential in NIT-1 cell clusters where AI4 T cells were attached. In the simultaneous control experiment where NIT-1 cells were co-cultured with MHC mis-matched human lymphocyte Jurkat cells, mitochondrial membrane potential remained intact. This technique can be used to observe real-time changes in mitochondrial membrane potential in cells under attack of cytotoxic lymphocytes, cytokines, or other cytotoxic reagents.

Cell-mediated lymphocytotoxicity (CML) assays can be used to test autoreactive responses and study mechanisms of cell death in vitro. However, using live-cell confocal microscopic imaging techniques with fluorescent dyes, the type and kinetics of cell death as well as the pathways utilized can be studied in greater detail.

β细胞死亡介导细胞毒性T淋巴细胞的方法来评估

Type 1 diabetes (T1D) is a T cell mediated autoimmune disease.  During the pathogenesis, patients become progressively more insulinopenic as 
insulin ...

科研

免疫与感染

piggyBac Transposon System Modification of Primary Human T Cells

The piggyBac transposon system is naturally active, originally derived from the cabbage looper moth1,2. This non-viral system is plasmid based, most commonly utilizing two plasmids with one expressing the piggyBac transposase enzyme and a transposon plasmid harboring the gene(s) of interest between inverted repeat elements which are required for gene transfer activity. PiggyBac mediates gene transfer through a "cut and paste" mechanism whereby the transposase integrates the transposon segment into the genome of the target cell(s) of interest. PiggyBac has demonstrated efficient gene delivery activity in a wide variety of insect1,2, mammalian3-5, and human cells6 including primary human T cells7,8. Recently, a hyperactive piggyBac transposase was generated improving gene transfer efficiency9,10.
Human T lymphocytes are of clinical interest for adoptive immunotherapy of cancer11. Of note, the first clinical trial involving transposon modification of human T cells using the Sleeping beauty transposon system has been approved12. We have previously evaluated the utility of piggyBac as a non-viral methodology for genetic modification of human T cells. We found piggyBac to be efficient in genetic modification of human T cells with a reporter gene and a non-immunogenic inducible suicide gene7. Analysis of genomic integration sites revealed a lack of preference for integration into or near known proto-oncogenes13. We used piggyBac to gene-modify cytotoxic T lymphocytes to carry a chimeric antigen receptor directed against the tumor antigen HER2, and found that gene-modified T cells mediated targeted killing of HER2-positive tumor cells in vitro and in vivo in an orthotopic mouse model14. We have also used piggyBac to generate human T cells resistant to rapamycin, which should be useful in cancer therapies where rapamycin is utilized15.
Herein, we describe a method for using piggyBac to genetically modify primary human T cells. This includes isolation of peripheral blood mononuclear cells (PBMCs) from human blood followed by culture, gene modification, and activation of T cells. For the purpose of this report, T cells were modified with a reporter gene (eGFP) for analysis and quantification of gene expression by flow cytometry.
PiggyBac can be used to modify human T cells with a variety of genes of interest. Although we have used piggyBac to direct T cells to tumor antigens14, we have also used piggyBac to add an inducible safety switch in order to eliminate gene modified cells if needed7. The large cargo capacity of piggyBac has also enabled gene transfer of a large rapamycin resistant mTOR molecule (15 kb)15. Therefore, we present a non-viral methodology for stable gene-modification of primary human T cells for a wide variety of purposes.

piggyBac Transposon System Modification of Primary Human T Cells

We describe a method to genetically modify primary human T cells with a transgene using the non-viral piggyBac transposon system. T cells modified to using the piggyBac transposon system exhibit stable transgene expression.

piggyBac转座子初级人类T细胞系统改造

The piggyBac transposon system is naturally active, originally derived from the cabbage looper moth1,2. This non-viral system is plasmid based, most ...

A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring cells. Of interest, only few assays are capable of specifically probing such interactions directly in living cells. Here, we present an assay to measure the binding of proteins expressed at the surfaces of neighboring cells, at cell-cell contacts. This assay consists of two steps: mixing of cells expressing the proteins of interest fused to different fluorescent proteins, followed by fluorescence fluctuation spectroscopy measurements at cell-cell contacts using a confocal laser scanning microscope. We demonstrate the feasibility of this assay in a biologically relevant context by measuring the interactions of the amyloid precursor-like protein 1 (APLP1) across cell-cell junctions. We provide detailed protocols on the data acquisition using fluorescence-based techniques (scanning fluorescence cross-correlation spectroscopy, cross-correlation number and brightness analysis) and the required instrument calibrations. Further, we discuss critical steps in the data analysis and how to identify and correct external, spurious signal variations, such as those due to photobleaching or cell movement.
In general, the presented assay is applicable to any homo- or heterotypic protein-protein interaction at cell-cell contacts, between cells of the same or different types and can be implemented on a commercial confocal laser scanning microscope. An important requirement is the stability of the system, which needs to be sufficient to probe diffusive dynamics of the proteins of interest over several minutes.

This protocol describes a fluorescence fluctuation spectroscopy-based approach to investigate interactions among proteins mediating cell-cell interactions, i.e. proteins localized in cell junctions, directly in living cells. We provide detailed guidelines on instrument calibration, data acquisition and analysis, including corrections to possible artefact sources.

细胞细胞接触物蛋白质-蛋白质相互作用的荧光波动光谱测定

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring ...

生物化学

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

从快速荧光成像在分子扩散法对活细胞的膜在商业显微镜

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

生物工程

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ranging from nanometers to micrometers and microseconds to minutes, respectively. Such a broad range of biological processes challenges conventional microscopy approaches. Here, we detail the procedure for implementing spot variation Fluorescence Correlation Spectroscopy (svFCS) measurements using a classical fluorescence microscope that has been customized. The protocol includes a specific performance check of the svFCS setup and the guidelines for molecular diffusion measurements by svFCS on the plasma membrane of living cells under physiological conditions. Additionally, we provide a procedure for disrupting plasma membrane raft nanodomains by cholesterol oxidase treatment and demonstrate how these changes in the lateral organization of the plasma membrane might be revealed by svFCS analysis. In conclusion, this fluorescence-based method can provide unprecedented details on the lateral organization of the plasma membrane with the appropriate spatial and temporal resolution.

This article aims to present a protocol on how to build a spot variation Fluorescence Correlation Spectroscopy (svFCS) microscope to measure molecular diffusion at the plasma membrane of living cells.

点变异荧光相关光谱用于分析活细胞质膜上的分子扩散

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ...

Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

We introduce a new method to measure the lateral diffusivity of a surfactant monolayer at the fluid-fluid interface, called fluorescence recovery after merging (FRAM). FRAM adopts the same principles as the fluorescence recovery after photobleaching (FRAP) technique, especially for measuring fluorescence recovery after bleaching a specific area, but FRAM uses a drop coalescence instead of photobleaching dye molecules to induce a chemical potential gradient of dye molecules. Our technique has several advantages over FRAP: it only requires a fluorescence microscope rather than a confocal microscope equipped with high power lasers; it is essentially free from the selection of fluorescence dyes; and it has far more freedom to define the measured diffusion area. Furthermore, FRAM potentially provides a route for studying the mixing or inter-diffusion of two different surfactants, when the monolayers at a surface of droplet and at a flat air/water interface are prepared with different species, independently.

We present a new technique to measure the lateral diffusion of a surface active species at the fluid-fluid interface by merging a droplet monolayer onto a flat monolayer.

合并一个液滴后荧光恢复来衡量磷脂单层的二维扩散

We introduce a new method to measure the lateral diffusivity of a surfactant monolayer at the fluid-fluid interface, called fluorescence recovery after ...

Dual-Color Fluorescence Cross-Correlation Spectroscopy to Study Protein-Protein Interaction and Protein Dynamics in Live Cells

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques. In dual-color FCCS, where the fluctuations in fluorescence intensity represent the dynamic &#34;fingerprint&#34; of the respective fluorescent biomolecule, we can probe co-diffusion or binding of the receptors. FRET, with its high sensitivity to molecular distances, serves as a well-known &#34;nanoruler&#34; to monitor intramolecular changes. Taken together, conformational changes and key parameters such as local receptor concentrations and mobility constants become accessible in cellular settings.
Quantitative fluorescence approaches are challenging in cells due to high noise levels and the vulnerability of the sample. Here we show how to perform this experiment, including the calibration steps using dual-color labeled &#946;2-adrenergic receptor (&#946;2AR) labeled with eGFP and SNAP-tag-TAMRA. A step-by-step data analysis procedure is provided using open-source software and templates that are easy to customize.
Our guideline enables researchers to unravel molecular interactions of biomolecules in live cells in situ with high reliability despite the limited signal-to-noise levels in live cell experiments. The operational window of FRET and particularly FCCS at low concentrations allows quantitative analysis at near-physiological conditions.

We present an experimental protocol and data analysis workflow to perform live cell dual-color fluorescence cross correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques.

双色荧光互相关光谱研究活细胞中蛋白质-蛋白质相互作用和蛋白质动力学

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance ...

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)

In the past fifteen years the notion that cell membranes are not homogenous and rely on microdomains to exert their functions has become widely accepted. Lipid rafts are membrane microdomains enriched in cholesterol and sphingolipids. They play a role in cellular physiological processes such as signalling, and trafficking1,2 but are also thought to be key players in several diseases including viral or bacterial infections and neurodegenerative diseases3.
Yet their existence is still a matter of controversy4,5. Indeed, lipid raft size has been estimated to be around 20 nm6, far under the resolution limit of conventional microscopy (around 200 nm), thus precluding their direct imaging. Up to now, the main techniques used to assess the partition of proteins of interest inside lipid rafts were Detergent Resistant Membranes (DRMs) isolation and co-patching with antibodies. Though widely used because of their rather easy implementation, these techniques were prone to artefacts and thus criticized7,8. Technical improvements were therefore necessary to overcome these artefacts and to be able to probe lipid rafts partition in living cells.
Here we present a method for the sensitive analysis of lipid rafts partition of fluorescently-tagged proteins or lipids in the plasma membrane of living cells. This method, termed Fluorescence Correlation Spectroscopy (FCS), relies on the disparity in diffusion times of fluorescent probes located inside or outside of lipid rafts. In fact, as evidenced in both artificial membranes and cell cultures, probes would diffuse much faster outside than inside dense lipid rafts9,10. To determine diffusion times, minute fluorescence fluctuations are measured as a function of time in a focal volume (approximately 1 femtoliter), located at the plasma membrane of cells with a confocal microscope (Fig. 1). The auto-correlation curves can then be drawn from these fluctuations and fitted with appropriate mathematical diffusion models11.
FCS can be used to determine the lipid raft partitioning of various probes, as long as they are fluorescently tagged. Fluorescent tagging can be achieved by expression of fluorescent fusion proteins or by binding of fluorescent ligands. Moreover, FCS can be used not only in artificial membranes and cell lines but also in primary cultures, as described recently12. It can also be used to follow the dynamics of lipid raft partitioning after drug addition or membrane lipid composition change12.

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy FCS

A technique to probe the lipid raft partitioning of fluorescent proteins at the plasma membrane of living cells is described. It takes advantage of the disparity in diffusion times of proteins located inside or outside of lipid rafts. Acquisition can be performed dynamically in control conditions or after drug addition.

脂筏的测定分区在活细胞中的荧光标记探针的荧光相关光谱（FCS）

In the past fifteen years the notion that cell membranes are not homogenous and rely on microdomains to exert their functions has become widely accepted. ...

生物学

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Particle tracking on a video sequence and the posterior analysis of their trajectories is nowadays a common operation in many biological studies. Using the analysis of cell membrane receptor clusters as a model, we present a detailed protocol for this image analysis task using Fiji (ImageJ) and Matlab routines to: 1) define regions of interest and design masks adapted to these regions; 2) track the particles in fluorescence microscopy videos; 3) analyze the diffusion and intensity characteristics of selected tracks. The quantitative analysis of the diffusion coefficients, types of motion, and cluster size obtained by fluorescence microscopy and image processing provides a valuable tool to objectively determine particle dynamics and the consequences of modifying environmental conditions. In this article we present detailed protocols for the analysis of these features. The method described here not only allows single-molecule tracking detection, but also automates the estimation of lateral diffusion parameters at the cell membrane, classifies the type of trajectory and allows complete analysis thus overcoming the difficulties in quantifying spot size over its entire trajectory at the cell membrane.

Here, we present a protocol for single particle tracking image analysis that allows quantitative evaluation of diffusion coefficients, types of motion and cluster sizes of single particles detected by fluorescence microscopy.

用荧光显微镜分析膜受体扩散和簇簇的图像处理协议

Particle tracking on a video sequence and the posterior analysis of their trajectories is nowadays a common operation in many biological studies. Using ...

Easy Measurement of Diffusion Coefficients of EGFP-tagged Plasma Membrane Proteins Using k-Space Image Correlation Spectroscopy

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new insights to plasma membrane protein function and regulation. Recently, k-Space Image Correlation Spectroscopy (kICS)1&#160;was developed to enable routine measurements of diffusion coefficients directly from images of fluorescently tagged plasma membrane proteins, that avoided systematic biases introduced by probe photophysics. Although the theoretical basis for the analysis is complex, the method can be implemented by nonexperts using a freely available code to measure diffusion coefficients of proteins. kICS calculates a time correlation function from a fluorescence microscopy image stack after Fourier transformation of each image to reciprocal (k-) space. Subsequently, circular averaging, natural logarithm transform and linear fits to the correlation function yields the diffusion coefficient. This paper provides a step-by-step guide to the image analysis and measurement of diffusion coefficients via kICS.
First, a high frame rate image sequence of a fluorescently labeled plasma membrane protein is acquired using a fluorescence microscope. Then, a region of interest (ROI) avoiding intracellular organelles, moving vesicles or protruding membrane regions is selected. The ROI stack is imported into a freely available code and several defined parameters (see Method section) are set for kICS analysis. The program then generates a &#34;slope of slopes&#34; plot from the k-space time correlation functions, and the diffusion coefficient is calculated from the slope of the plot. Below is a step-by-step kICS procedure to measure the diffusion coefficient of a membrane protein using the renal water channel aquaporin-3 tagged with EGFP as a canonical example.

This paper provides a step by step guide to the fluctuation analysis technique k-Space Image Correlation Spectroscopy (kICS) for measuring diffusion coefficients of fluorescently labeled plasma membrane proteins in live mammalian cells.

绿色荧光蛋白标记的质膜蛋白质的扩散系数的简易测量采用K空间图像相关光谱

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new ...