This work is supported in part by NIH-P41 P41-RRO3155 and NIH P50-GM076516 (grant to EG), and Fondazione Monte dei Paschi di Siena (grant to FB).

1，系统校准<ol><li>点扩散函数（PSF）的校准<ol><li>稀释10微升的30纳米荧光珠溶液（约5μm）在90微升蒸馏水中，然后超声处理20分钟，该溶液中。切成正方形（1 1cm×1cm的）一块琼脂糖凝胶（3％）和存款10微升在凝胶顶部的溶液中。推翻了一块凝胶上2厘米的培养皿底部的玻璃和挤压玻璃上的下降。 </li><li>打开采集设置，把样品中的持有人，将相机的曝光和EMgain（100毫秒和1000都不错的参数，但优化根据系统），并等待相机冷却下来。 </li><li>将相机的曝光为100毫秒，相机EMgain到1000，采集模式帧传输，100重复和自动保存设置。 </li><li>使用目镜和透射的光聚焦在凝胶上的边界，然后移动目标的凝胶的中心，调整焦距和站RT激光校准程序（在拉斯维加斯的AF，选择&#39;全内反射荧光设置"，然后按自动调整过程）。 </li><li>找到的视场与分离的单斑点，准确地集中于较亮的点（即通常代表珠子聚集体）作为参照，取得100帧，以便获得多个单点重复步骤5-6次。 </li><li>导入所获得的一系列的数据处理程序，并在时间平均化叠层（ 图1A），并选择单个孤立的珠子。小心选择最小的，以避免粒子的聚集体。 </li><li>适合使用命令"gaussfit"所选择的光强分布（单珠信息的一例示于图1B）用高斯函数（在ICS-Matlab的工具中的材料在Matlab）。通过检查得到的残差检验的拟合优度（拟合高斯分布与相应的残差的一个例子，提出íQ 图1B）。 </li></ol></li><li>摄像机标定<ol><li>打开相机电源，等待摄像机冷却下来。将摄像头采集的设置（ 即 ，对于所使用的摄像头，我们将曝光到0.5毫秒，相机EMgain到1000，采集模式，以裁切模式，投资回报率的大小为32×128，万家重复），并开始采集摄像头背景信号。 </li><li>导入收购框架系列的数据处理程序。计算并检查在每个像素的平均强度，以确认该照相机的背景是在芯片的选择的区域大致平坦。在裁切模式，除去第一和最后几水平线（3至10根据ROI的大小）对每一帧，因为相机的背景通常是偏向于边界线。 </li><li>创建值的直方图（也定义了电子水准仪，DL）中获得的图像栈（在Matlab中使用命令"HIST"），并绘制对数产生的频率（在Matlab使用semilogy命令）。 DL分配的相机背景的一个例子示于图2。 注:如果相机运作良好，剧情会显示约高斯峰（对数尺度的抛物线轮廓），代表相关零光子之后的指数衰减（以对数刻度负斜率的线值的分布），表示相关联的1光子（ 图2）的值的分布。特别是，中心和高斯函数的方差表示相机的偏移和误差，分别，而指数部分的衰减常数表示由相机对每个单光子分配的DL的估计。在Matlab中使用脚本的一节"CalibrateCamera"的配套教材。 </li><li>重复上述操作所有选定相机EMGain和增益。 </li></ol></li></ol> 2，标记细胞的制备<ol><li>以制备所需的脂质掺入36的脂质体，溶解分别为1mg DOPE（1,2-dioleoyl- SN -glycero-3-磷酸乙醇胺），1毫克DOTAP（1,2 -二油酰-3 -三甲基铵-丙烷）的和于1ml氯仿中1毫克PPE-ATTO488的。混合在一起加入0.5ml DOPE溶液，0.5毫升DOTAP溶液，并加入25μl的PPE-ATTO488溶液并在真空下干燥24小时。加入0.5毫升HEPES缓冲液为20mM的，涡旋15分钟，超声处理15分钟，在40℃下。 </li><li>以制备的细胞，用PBS洗3次汇合的CHO-K1（中国仓鼠卵巢）的P100菜，在培养箱中加入1 ml胰蛋白酶和商店的5分钟。暂停分离的细胞中加入9毫升DMEM / F12培养基补充有FBS的10％，种子150微升的细胞溶液中含有800微升的同一种培养基的培养皿中。 </li><li>商店在培养箱中培养24小时，在37℃和5％CO 2。脂质结合，取代500细胞培养基微升无血清的培养基中; 30分钟后，加入2微升的脂质体溶液; 15分钟后洗涤用PSB并添加新的DMEM / F12培养基以进行成像。 </li><li>对于转染，根据使用转铁蛋白-GFP质粒，并存储24小时在恒温箱成像之前的Lipofectamine协议（制造商的说明）转染细胞。 </li></ol> 3，数据采集<ol><li>安装准备<ol><li>为了温控显微镜，实验前24小时开机的孵化器。 </li><li>为了应用最快达到的采集时间，在裁剪传感器模式工作（见介绍），并使用第一相机的成像（相机1）和第二相机来选择小区（相机2）。安装配置的方案呈现在补充图S1。然后，对准两个相机开启显微镜和等待相机冷却下来。 </li><li>将两款相机的参数，透射光成像（ 即 </em&gt;，20毫秒的曝光时间，1 EM增益），并把显微镜明场模式。 </li><li>将样品在支架和重点用目镜，送光相机1，轻轻推了开衩让光只用于细胞成像（这里是32×32像素的投资回报率）的投资回报率。 </li><li>移动一个单元格选定区域和发送光相机2，然后绘制在控制摄像头2为了有一个参考该软件的投资回报率。 </li></ol></li><li>成像（ 图3A） <ol><li>首先，根据您的设​​置的程序对齐全内反射荧光激光。在我们的设置中，选择"全内反射荧光设置"，并开始自动调整过程。当激光对准设置的穿透深度为70nm（约70°）。 </li><li>设置曝光时间为70毫秒，EMGain 100两个摄像机1和摄像机2;然后，选择用相机1的单元格，然后发送光相机2，准确地聚焦在细胞膜上。坐落在加利福尼亚州的最低曝光MERA 2 1000 EMGain，裁剪传感器模式，10 5的重复和设置自动保存为配合文件（灵活图像传输系统，一种格式，可以很容易地进行管理）。 </li><li>开始采集记录的图像系列。释放增益和裁剪方式，以使温度稳定取得了新的电池前，那么为了获得8-10细胞重复最后两个步骤。 </li></ol></li></ol>从影像学4，计算的均方位移（I MSD） 注意:下面的协议可以被直接应用到原始数据。同时，在整个协议都有效在Matlab和在SimFCS模拟数据采集。链接到相应的教程可以在"材料"部分中找到。 <ol><li>计算用Matlab <ol><li>导入使用ImportImageSeries脚本获取的系列Matlab的。使用共同计算各图像的平均亮度在时间mmand意味着在第一个2的尺寸和使用小区看到生成的载体。 </li><li>若漂白的10％以上存在时，丢弃该系列或删除它们的第一部分。如果是较低的，尝试纠正对相关函数的影响中减去每个图像的平均强度，如37之前所示。 </li><li>通过使用平均值在第三维度计算每个像素的平均强度和见得到的图像。 注意:要求特别注意以避免人为的相关性。事实上，如前面对于类似的技术38，单元格边框以及聚焦囊泡所示可以引入很强的相关性。如果平均图像的检查结果显示单元格边框或失焦小泡，尽量排除参与，否则丢弃该收购的区域。要纠正这种不动结构的影响，从每个像素39减去平均时间上的强度。 </li><li>计算吨他的时空相关性（G（ξ，χ，τ））的使用功能CalculateSTICScorrfunc。删除G（ξ，χ，0），因为由于在低光环境的散粒噪声的相关性主导G（0,0,0）;由于检测器的相关主导着G（±1,0,0），和粒子运动过程中的曝光时间可变形G（ξ，χ，τ）为τ= 0，通过增加测量的腰部（该效果消失为τ &gt; 0）34。 </li><li>平均g用对数时间斌用"LogBinStack"功能的辅助材料以减少噪声，然后（ξ，χ，τ&gt; 0）满足所产生的G（ξ，χ，τ）使用功能"gaussfit"在材料的ICS与Matlab工具恢复的I MSD（结果数组的第二列）。 </li><li>积所得的腰部σ（τ）2（ⅰMSD）作为时间的函数。如果数据过于嘈杂，设法增加acqu数IRED帧，增加激光功率，平均多个G（ξ，χ，τ）在一起。 </li></ol></li><li>计算由SimFCS <ol><li>与使用ImageJ BioFormat进口商插件打开文件获取并保存后天系列为TIFF序列。 </li><li>打开SimFCS并选择RICS工具，然后选择文件&gt;导入多张图片（补充图S2）。 </li><li>选择飞度，插入正确的采集参数，并关闭窗口合身（补充图S3）。 </li><li>选择显示&gt;平均强度&gt; CH1和验证漂白的存在（补充图S4）。 </li><li>若漂白的10％以上是本丢弃的系列，或者如果它是可能的负载再次在图像序列中除去该系列的第一部分。 </li><li>如果漂白是低于10％，选择工具&gt;我的MSD&gt;设置参数，选中"使用移动平均线"，在左边一个在ROI面板中设置赭帧的移动平均关注的对应时间比特征扩散时间增加（为粒子在1微米2秒移动-1 10秒的时间是一个很好的移动平均） </li><li>选择工具&gt; IMSD&gt;计算ìMSD（补充图S5），并配合和记事簿导出的I MSD（补充图六 ）。 </li></ol></li></ol>从I MSD 5计算扩散法<ol><li>适合的前几个点来推断的截距（σ0 2）（5分通常是足够的，但更多的点可以安装如果它们表现出非线性行为），该值与先前测量的PSF 2比较。如果它们是可比较的，孤立的荧光动力学正紧随其后。与此相反，如果σ0 2 &gt;&gt; PSF 2试图获取更快，以确保没有任何隐藏的动力是目前的34。 </li><li>计算表观扩散系数（D 应用程序 ），并使用等式3和4（参见引言）的平均位移（R）。 </li><li> D地块的应用程序为R的函数来获得一个扩散定律什么是衡量基于FCS的12（ 图3D）点的变化相媲美。 </li></ol>

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The authors have nothing to disclose.

单粒子追踪（SPT）表示的研究分子动力学中最常见的策略之一，它具有测量粒子轨迹的显着优点。这又允许探测在一个复杂的系统，即使少量标记粒子的行为。然而，为了达到这个优点SPT通常需要将探头和非常明亮的标签的密度低。具体地讲，以获得高的时间分辨率（微秒范围）无机探针通常需要（ 例如，量子点或金属纳米粒子）:在这种情况下的产量，标签和插入一个复杂的过程进系统 ?...

从原来的"流体镶嵌"模型歌手和尼科尔森开始，细胞质膜的画面不断在过去几十年更新，以包括细胞骨架和脂质域1,2的新兴角色。 第一观察由荧光漂白恢复（FRAP）揭开该膜蛋白的显著分数是不动的3-5后得到。这些开创性的研究，虽然非常丰富，受到FRAP设置在空间（微米）相对较差的分辨率和时间（秒）。此外，作为一个统计平均测量，FRAP缺乏使单分子行为的信息。 在这种情况下，有可能以特别标示具有非常明亮的标记（允许在扩散过程中的一个分子在一个时间的研究）的单个分子已经非常成功。特别是，通过推动单粒子追踪（SPT）的方法来微秒的时间尺度，久住，等脂质和蛋白质动力学的未知功能，极大地促进了表彰肌动蛋白为基础的膜骨架的作用在细胞膜的生理6 人获得了进入的时间分辨率，7。这些发现产生了所谓的"尖桩和栅栏"的模式，在其中的脂质和蛋白质的扩散是通过基于肌动蛋白骨架的调节。然而，为了能够访问大量的由SPT许多实验的问题所提供的信息必须得到解决。具体地讲，标记过程通常是通过许多步骤，如标记物种进入该系统的生产，纯化和介绍组成。此外，大的标签，如量子点，金属纳米颗粒，通常需要达到亚毫秒级的时间尺度与目标分子的标记的交联无法避免在许多情况下。最后，许多轨迹已被记录，以符合统计标准和伴随低密度标签的需要，以允许跟踪。 相比SPT，荧光相关光谱（FCS），克服许多这些缺点，是一种非常有前途的方法来研究分子动力学。事实上，FCS的效果很好也有暗淡而密的标签，使研究荧光蛋白标记的分子动力学瞬时转染细胞。此外，它允许达到较高的数据在有限的时间。最后，尽管标签的"高"密度FCS提供单个分子的信息。感谢所有这些特性，FCS是一个非常简单的方法，并已被广泛应用于研究脂类和蛋白质动力学无论是在模型膜和活细胞8-10。许多不同的方法已经被提出以提高FCS的揭示分子扩散的细节的能力。例如，它是sh的自己通过对不同大小的观察区域进行的FCS可以定义分子运动11,12的"FCS扩散法"的启发隐藏的功能。除了 ​​被大小不一，重点领域也重复13，移动沿线14-20或共轭快速相机21,22空间。使用这些"时空"的相关办法，几个膜元件相关的生物学参数上都细胞膜的模型与实际的生物学者，由此制得的洞察膜空间组织进行了定量描述。 然而，在所有的FRAP和FCS应用到目前为止描述的焦点区域的大小代表了在空间分辨率的限制，无法克服。几个超分辨率成像方法近来已经开发绕过此限制。有些是基于定位的精度，如随机光学重建显微镜（STORM）&lt;SUP&gt; 23,24，光活化定位显微镜（PALM）25，荧光PALM（FPALM）26，和单粒子跟踪PALM（sptPALM）27:比较大的值，在每个快照需要的光子，但是，限制的时间分辨率这些方法中的至少几毫秒，从而妨碍了它们在体内的适用性。 与此相反，一个有前途的替代超分辨率成像已被打开的空间调制与受激发射损耗的方法（STED或可逆饱和光荧光跃迁（RESOLFT））28,29的荧光发射。这些方法结合起来观察体积的成形以及低于衍射极限与使用快速扫描显微镜和检测系统的可能性。在用荧光波动分析组合，STED显微镜允许直接探测脂质和p的纳米尺度的时空动力学roteins活细胞膜30,31。 相同的物理量的受激发射损耗系显微镜可以通过改性时空图像相关光谱（STICS 32,33）方法，该方法适合于荧光标记的膜蛋白和/或脂 ​​类中的活细胞的动力学的研究得到而由商业显微镜。实验方案这里介绍的是由几个步骤组成。第一个要求在膜感兴趣区域的快速成像。然后，将得到的图像的堆栈用来计算平均值的空间 - 时间相关性的函数。通过拟合一系列的相关函数，该分子"扩散法"，可直接从成像获得的表观扩散系数（D 应用程序 ）的形式- 比 -平均位移曲线图。该图的关键取决于由分子探索的环境，并允许直接识别的实际扩散模式的感兴趣的脂质/蛋白质。 更详细地，如先前所示图34中，获取的图像序列的时空自相关函数的关键取决于移动中所收集的图像序列的分子动力学（请注意，相同的推理也可以从行采集应用凡在空间只是一个维度考虑）。特别地，我们定义的相关函数为: <img fo:content-width="2.3in" src="/files/ftp_upload/51994/51994eq1.jpg" width="230" /> （1） 其中<img fo:content-width=".5in" src="/files/ftp_upload/51994/xyt.jpg" width="50" />表示测得的荧光强度中的位置x，y和时间t， <img fo:content-width=".08in" src="/files/ftp_upload/51994/e.jpg" width="8" />和<img fo:content-width=".1in" src="/files/ftp_upload/51994/x.jpg" width="10" />表示在x的距离和分别为Y方向， <img fo:content-width=".1in" src="/files/ftp_upload/51994/t.jpg" width="10" />表示的时间差，并<img fo:content-width=".2in" src="/files/ftp_upload/51994/brackets.jpg" width="20" />表示平均。这个函数可以表示为: <img fo:content-width="2.3in" src="/files/ftp_upload/51994/51994eq2.jpg" width="230" /> （2） 其中"N"表示在该观察区域分子的平均数目， <img fo:content-width=".10in" src="/files/ftp_upload/51994/circlex.jpg" width="10" />表示空间中的卷积运算，并<img fo:content-width=".5in" src="/files/ftp_upload/51994/ex.jpg" width="50" />代表器乐腰部的自相关。后者可以被解释为对如何将单个发射器的光子被摊开在空间的量度，由于光/记录设置程序（所谓的点扩散函数，PSF，基因涨势以及由高斯函数近似）。最后， <img fo:content-width=".5in" src="/files/ftp_upload/51994/ext.jpg" width="50" />代表的概率找到一个粒子的距离<img fo:content-width=".10in" src="/files/ftp_upload/51994/e.jpg" width="10" />和<img fo:content-width=".10in" src="/files/ftp_upload/51994/x.jpg" width="10" />延时后， <img fo:content-width=".10in" src="/files/ftp_upload/51994/t.jpg" width="10" /> 。如果我们考虑扩散动力学，粒子随机移动在各个方向和净通量是不存在的，这个功能也很好用高斯函数，其中的差异，可以认定为运动粒子的均方位移（MSD）的近似。因此，相关函数的腰部（也称为<img fo:content-width=".3in" src="/files/ftp_upload/51994/2t.jpg" width="30" /> ），可以被定义为颗粒的MSD的总和和器乐腰部，并且可以通过高斯拟合来测定婷的相关函数为每个时间延迟。在测量电流I MSD可以用来计算移动分子的表观扩散系数<img fo:content-width=".4in" src="/files/ftp_upload/51994/dappt.jpg" width="40" />和平均位移<img fo:content-width=".4in" src="/files/ftp_upload/51994/rt.jpg" width="40" />如: <img fo:content-width="1.7in" src="/files/ftp_upload/51994/51994eq3.jpg" width="170" /> （3） <img fo:content-width="1.7in" src="/files/ftp_upload/51994/51994eq4.jpg" width="170" /> （4） 很少考虑对实验装置可以用来引导读者在以下几节。为了选择性地激发荧光团上的活细胞，我们将使用全内反射（TIR）的照明，使用市售的TIR荧光的基膜（TIRF）显微镜（细节可在材料部分中找到）。此外，为了收集日ê荧光，我们将使用高倍率物镜（100X NA 1.47，高数值孔径需要全内反射荧光照明）和EMCCD摄像头（像素的物理尺寸上的芯片16微米）。以达到100nm的像素大小，我们应用1.6X的附加放大率透镜。如下面讨论的，将需要低于1毫秒的时间分辨率来适当地描述的快速膜脂质的动力学低于100nm。为了达到这个时间分辨率，我们需要选择的感兴趣区域（ROI）的区域比相机（512×512）的整个芯片更小。在这种方式中，相机将读取线增加时间分辨率的数目可以减少。然而，在此读出机制的帧时间将通过从曝光的电荷转移到读出芯片的照相机上需要与通常以毫秒为512×512像素的EMCCD的顺序的时间限制。要打败这个限制，一个新兴的技术可以转移的投资回报率，仅行而不是整个框架，W第i个实际有效减少暴露的芯片尺寸（称为我们的EMCCD七分传感器模式）。对于这种配置是有效的，必须将ROI的外片覆盖的一对狭缝安装在光路中的。由于这种设置的时间分辨率降低到10 -4秒就可以实现。但是，请注意，这种方法可以与许多不同的实验装置，为"讨论"一节中的说明。 该方法的演示将在活细胞中提供，通过使用这两个标记的一个ATTO488 1 -棕榈酰基-2 -羟基- SN -glycero-3-磷酸乙醇胺（ATTO488-PPE）和转铁蛋白受体的GFP-标记的变体（GFP- TFR）。在ATTO488-PPE的情况下，这种方法可以成功地回收了几乎常数D 的应用程序作为平均位移表示较自由扩散的功能，如先前报道30,35。相比之下，TFR-GFP呈减少ð <suB&gt;应用程序的平均位移的功能，提示局部密闭扩散6。此外，在后者的情况下也能够进行量化的局部扩散常数和平均禁闭面积比在膜面内的许多微米。

<table><tbody><tr><td>iXon Ultra 897</td><td>Andor</td><td>DU-897U-CS0</td><td></td></tr><tr><td>Solis</td><td>Andor</td><td></td><td></td></tr><tr><td>CHO-K1</td><td>ATCC</td><td>CCL-61</td><td></td></tr><tr><td>ATTO 488 labeled PPE</td><td>ATTO-TEC GmbH</td><td>AD 488-151</td><td></td></tr><tr><td>DOPE</td><td>Avanti Polar Lipids, Inc.</td><td>850725</td><td></td></tr><tr><td>DOTAP</td><td>Avanti Polar Lipids, Inc.</td><td>890890</td><td></td></tr><tr><td>100x Penicillin-Streptomycin-Glutamine</td><td>Gibco</td><td>10378-016</td><td></td></tr><tr><td>DMEM/F-12</td><td>Gibco</td><td>21331</td><td></td></tr><tr><td>FBS</td><td>Gibco</td><td>10082147</td><td></td></tr><tr><td>HEPES</td><td>Gibco</td><td>15630-106&amp;nbsp;</td><td></td></tr><tr><td>PBS</td><td>Gibco</td><td>10010-023</td><td></td></tr><tr><td>SimFCS 3.0</td><td>Globals Software</td><td></td><td>the software can be downloaded here: http://www.lfd.uci.edu/globals/</td></tr><tr><td>DMI6000 with TIRF modulus</td><td>Leica</td><td></td><td></td></tr><tr><td>LAS AF</td><td>Leica</td><td></td><td></td></tr><tr><td>Lipofectamine 2000</td><td>Lipofectamine</td><td>11668019</td><td></td></tr><tr><td>Matlab</td><td>MathWork</td><td></td><td></td></tr><tr><td>ImageJ</td><td>NIH</td><td></td><td></td></tr><tr><td colspan="4">[header]</td></tr><tr><td>C-terminal GFP tagged Tranferrin Receptor</td><td>OriGene</td><td>RG200980</td><td></td></tr><tr><td>Agar</td><td>Sigma Aldrich</td><td>A5306</td><td></td></tr><tr><td>Chloroform</td><td>Sigma Aldrich</td><td>528730</td><td></td></tr><tr><td>Latex beads, fluorescent yellow-green, 30 nm</td><td>Sigma Aldrich</td><td>L5155</td><td></td></tr><tr><td>SONICA Ultrasonic Cleaners</td><td>SOLTEC</td><td>ETH S3</td><td></td></tr><tr><td>Petri Dishes</td><td>Willco</td><td>GWSt-3522</td><td></td></tr><tr><td>Bio-Format importer for Matlab</td><td></td><td></td><td>http://www.openmicroscopy.org/site/support/bio-formats5/users/matlab/</td></tr><tr><td>ICS-MatLab Tools</td><td></td><td></td><td>&lt;a href=&quot;https://www.cellmigration.org/resource/imaging/software/ICSMATLAB_28-02-06.zip&quot;&gt;https://www.cellmigration.org/resource/imaging/software/ICSMATLAB_28-02-06.zip&lt;/a&gt;</td></tr><tr><td>Simulation by Matlab Tutorial</td><td></td><td></td><td>https://www.cellmigration.org/resource/imaging/icsmatlab/ICSTutorial.html</td></tr><tr><td>Simulation by SimFCS Tutorial</td><td></td><td></td><td>https://www.cellmigration.org/resource/imaging/ppt-pdf/RICS%20Simulations.ppt</td></tr></tbody></table>

from fast fluorescence imaging to molecular diffusion law on live cell membranes in a commercial microscope

它已成为越来越明显，空间分布和膜元件，如脂质和蛋白质的运动是关键因素在许多细胞功能的调节。然而，由于快速的动力学和所涉及的微小结构，非常高的时空分辨率，需要捕捉分子的真实行为。这里，我们提出的实验方案用于研究活细胞中以高时空分辨率荧光标记的质膜蛋白质和脂质的动态。值得注意的是，这种方法并不需要跟踪每个分子，但它计算使用的所有分子在膜中的一个给定区域的人口行为。其出发点是在膜上某一区域的快速成像。之后，一个完整的时空自相关函数计算在增加的时间延迟，例如每2，3中，n次重复关联采集的图像。因此能够证明该宽度的在增加的时间延迟作为粒子运动的函数，由于扩散空间自相关函数的增加的峰值。因此，串联的自相关函数的拟合使得能够提取实际蛋白质意味着从成像（IMSD）方位移，这里提出的表观扩散系数比平均位移的形式。这就产生了单分子与纳米精度的平均动态的定量看法。通过使用转铁蛋白受体（TFR）和一个ATTO488的GFP标记的变体标记的1 -棕榈酰基-2 -羟基- SN -glycero-3-磷酸乙醇胺（PPE），可以观察到的蛋白质和脂质扩散的时空调控上微米尺寸的膜的区域中的微至毫秒的时间范围内。

为了校准的仪器腰部，单个荧光纳米珠的图象可以作为在协议步骤1.1中描述为量度。这些珠的典型的荧光图像示于图1。强度分布由二维高斯函数拟合还给良好的残差，并允许测量仪器腰部在270nm处。这个值是在与由瑞利方程估计的预期衍射极限相吻合。该校准是没有必要的粒子动力学的测量，但它需要测量的表观粒度。 相机背景的典型频率分布示于图2。</s...

Watch this Scientific Journal Video about From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope at JoVE.com

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

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 ...

from-fast-fluorescence-imaging-to-molecular-diffusion-law-on-live

Research

JoVE Journal

Bioengineering

11.4K 次观看.  Scuola Normale Superiore. 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.

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

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Single-molecule localization microscopy probes the position and motions of individual molecules in living cells with tens of nanometer spatial and millisecond temporal resolution. These capabilities make single-molecule localization microscopy ideally suited to study molecular level biological functions in physiologically relevant environments. Here, we demonstrate an integrated protocol for both acquisition and processing/analysis of single-molecule tracking data to extract the different diffusive states a protein of interest may exhibit. This information can be used to quantify molecular complex formation in living cells. We provide a detailed description of a camera-based 3D single-molecule localization experiment, as well as the subsequent data processing steps that yield the trajectories of individual molecules. These trajectories are then analyzed using a numerical analysis framework to extract the prevalent diffusive states of the fluorescently labeled molecules and the relative abundance of these states. The analysis framework is based on stochastic simulations of intracellular Brownian diffusion trajectories that are spatially confined by an arbitrary cell geometry. Based on the simulated trajectories, raw single-molecule images are generated and analyzed in the same way as experimental images. In this way, experimental precision and accuracy limitations, which are difficult to calibrate experimentally, are explicitly incorporated into the analysis workflow. The diffusion coefficient and relative population fractions of the prevalent diffusive states are determined by fitting the distributions of experimental values using linear combinations of simulated distributions. We demonstrate the utility of our protocol by resolving the diffusive states of a protein that exhibits different diffusive states upon forming homo- and hetero-oligomeric complexes in the cytosol of a bacterial pathogen.

3D single-molecule localization microscopy is utilized to probe the spatial positions and motion trajectories of fluorescently labeled proteins in living bacterial cells. The experimental and data analysis protocol described herein determines the prevalent diffusive behaviors of cytosolic proteins based on pooled single-molecule trajectories.

单分子跟踪显微镜 - 确定细胞分子扩散状态的工具

Single-molecule localization microscopy probes the position and motions of individual molecules in living cells with tens of nanometer spatial and ...

科研

生物化学

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular level. To date the shear complexity of biological systems has caused precise single-molecule experimentation to be far too demanding, instead focusing on studies of single systems using relatively crude bulk ensemble-average measurements. However, many important processes occur in the living cell at the level of just one or a few molecules; ensemble measurements generally mask the stochastic and heterogeneous nature of these events. Here, using advanced optical microscopy and analytical image analysis tools we demonstrate how to monitor proteins within a single living bacterial cell to a precision of single molecules and how we can observe dynamics within molecular complexes in functioning biological machines. The techniques are directly relevant physiologically. They are minimally-perturbative and non-invasive to the biological sample under study and are fully attuned for investigations in living material, features not readily available to other single-molecule approaches of biophysics. In addition, the biological specimens studied all produce fluorescently-tagged protein at levels which are almost identical to the unmodified cell strains ("genomic encoding"), as opposed to the more common but less ideal approach for generating significantly more protein than would occur naturally ('plasmid expression'). Thus, the actual biological samples which will be investigated are significantly closer to the natural organisms, and therefore the observations more relevant to real physiological processes.

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Here we demonstrate the protocols for performing single-molecule fluorescence microscopy on living bacterial cells to enable functional molecular complexes to be detected, tracked and quantified.

可视化单分子络合物在体内使用高级荧光显微

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular ...

生物学

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, ...

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

Fluorescence correlation spectroscopy (FCS) is a powerful technique for studying the diffusion of molecules within biological membranes with high spatial and temporal resolution. FCS can quantify the molecular concentration and diffusion coefficient of fluorescently labeled molecules in the cell membrane. This technique has the ability to explore the molecular diffusion characteristics of molecules in the plasma membrane of immune cells in steady state (i.e., without processes affecting the result during the actual measurement time). FCS is suitable for studying the diffusion of proteins that are expressed at levels typical for most endogenous proteins. Here, a straightforward and robust method to determine the diffusion rate of cell membrane proteins on primary lymphocytes is demonstrated. An effective way to perform measurements on antibody-stained live cells and commonly occurring observations after acquisition are described. The recent advancements in the development of photo-stable fluorescent dyes can be utilized by conjugating the antibodies of interest to appropriate dyes that do not bleach extensively during the measurements. Additionally, this allows for the detection of slowly diffusing entities, which is a common feature of proteins expressed in cell membranes. The analysis procedure to extract molecular concentration and diffusion parameters from the generated autocorrelation curves is highlighted. In summary, a basic protocol for FCS measurements is provided; it can be followed by immunologists with an understanding of confocal microscopy but with no other previous experience of techniques for measuring dynamic parameters, such as molecular diffusion rates.

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 ...

免疫与感染

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze membrane fusion within eukaryotic cells. The SNARE protein family consists of about 36 different members. Specific intracellular transport routes are catalyzed by specific sets of 3 or 4 SNARE proteins that thereby contribute to the specificity and fidelity of membrane trafficking. However, studying the precise function of SNARE proteins is technically challenging, because SNAREs are highly abundant and functionally redundant, with most SNAREs having multiple and overlapping functions. In this protocol, a new method for the visualization of SNARE complex formation in live cells is described. This method is based on expressing SNARE proteins C-terminally fused to fluorescent proteins and measuring their interaction by F&#246;rster resonance energy transfer (FRET) employing fluorescence lifetime imaging microscopy (FLIM). By fitting the fluorescence lifetime histograms with a multicomponent decay model, FRET-FLIM allows (semi-)quantitative estimation of the fraction of the SNARE complex formation at different vesicles. This protocol has been successfully applied to visualize SNARE complex formation at the plasma membrane and at endosomal compartments in mammalian cell lines and primary immune cells, and can be readily extended to study SNARE functions at other organelles in animal, plant, and fungal cells.

This protocol describes a new method allowing for the quantitative visualization of complex formation of SNARE proteins, based on F&#246;rster resonance energy transfer, and fluorescence lifetime imaging microscopy.

荧光寿命成像显微镜观察细胞内圈套的贩运

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze ...

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. ...

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at characterizing the complex organization and dynamics of the plasma membrane at single-molecule level, by developing analytic tools dedicated to Single-Particle Tracking (SPT) at high density: Multiple-Target Tracing (MTT)1. Single-molecule videomicroscopy, offering millisecond and nanometric resolution1-11, allows a detailed representation of membrane organization12-14 by accurately mapping descriptors such as cell receptors localization, mobility, confinement or interactions.
We revisited SPT, both experimentally and algorithmically. Experimental aspects included optimizing setup and cell labeling, with a particular emphasis on reaching the highest possible labeling density, in order to provide a dynamic snapshot of molecular dynamics as it occurs within the membrane. Algorithmic issues concerned each step used for rebuilding trajectories: peaks detection, estimation and reconnection, addressed by specific tools from image analysis15,16. Implementing deflation after detection allows rescuing peaks initially hidden by neighboring, stronger peaks. Of note, improving detection directly impacts reconnection, by reducing gaps within trajectories. Performances have been evaluated using Monte-Carlo simulations for various labeling density and noise values, which typically represent the two major limitations for parallel measurements at high spatiotemporal resolution.
The nanometric accuracy17 obtained for single molecules, using either successive on/off photoswitching or non-linear optics, can deliver exhaustive observations. This is the basis of nanoscopy methods17 such as STORM18, PALM19,20, RESOLFT21 or STED22,23, which may often require imaging fixed samples. The central task is the detection and estimation of diffraction-limited peaks emanating from single-molecules. Hence, providing adequate assumptions such as handling a constant positional accuracy instead of Brownian motion, MTT is straightforwardly suited for nanoscopic analyses. Furthermore, MTT can fundamentally be used at any scale: not only for molecules, but also for cells or animals, for instance. Hence, MTT is a powerful tracking algorithm that finds applications at molecular and cellular scales.

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing MTT

Multiple-Target Tracing is a homemade algorithm developed for tracking individually labeled molecules within the plasma membrane of living cells. Efficiently detecting, estimating and tracing molecules over time at high-density provide a user-friendly, comprehensive tool to investigate nanoscale membrane dynamics.

测绘在细胞膜分子扩散，多目标跟踪（MTT）

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at ...

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 ...

用于基于 FLIM 的代谢和缺氧分析的多细胞球状体形成

Production and Multi-Parameter Live Cell Fluorescence Lifetime Imaging Microscopy (FLIM) of Multicellular Spheroids

Multicellular tumor spheroids are a popular 3D tissue microaggregate&#160;model for reproducing tumor microenvironment, testing and optimizing drug therapies&#160;and using bio- and nanosensors in a 3D context. Their ease of production, predictable size, growth, and observed nutrient and metabolite gradients are important to recapitulate the 3D niche-like&#160;cell microenvironment. However, spheroid heterogeneity and variability of their production methods can influence overall cell metabolism, viability, and drug response. This makes it difficult to choose the most appropriate&#160;methodology, considering the requirements in size, variability, needs of biofabrication, and use as in vitro 3D tissue models in stem and cancer cell biology. In particular, spheroid production can influence their compatibility with quantitative live microscopies, such as optical metabolic imaging, fluorescence lifetime imaging microscopy (FLIM), monitoring of spheroid&#160;hypoxia with nanosensors, or viability. Here, a number of conventional spheroid formation protocols are presented, highlighting their compatibility with the live widefield, confocal, and two-photon microscopies. The follow-up imaging to analysis&#160;pipeline with multiplexed autofluorescence FLIM and, using various types of cancer and stem cell spheroids, is also presented.

作者聚焦:使用荧光寿命成像显微镜标准化用于代谢和氧合分析的球状体形成方法

Here, we describe different multicellular spheroid formation methods to perform follow-up multi-parameter live cell microscopy. Using fluorescence lifetime imaging microscopy (FLIM), cellular autofluorescence, staining dyes, and nanoparticles, the approach for analysis of cell metabolism, hypoxia, and cell death in live three-dimensional (3D) cancer and stem cell-derived spheroids is demonstrated.

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜 （FLIM）

Multicellular tumor spheroids are a popular 3D tissue microaggregate&#160;model for reproducing tumor microenvironment, testing and optimizing drug ...

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

摘要

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单分子跟踪显微镜 - 确定细胞分子扩散状态的工具

可视化单分子络合物在体内使用高级荧光显微

点变异荧光相关光谱用于分析活细胞质膜上的分子扩散

由荧光相关光谱测量的一次淋巴细胞的细胞膜分子扩散

荧光寿命成像显微镜观察细胞内圈套的贩运

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）

测绘在细胞膜分子扩散，多目标跟踪（MTT）

用荧光显微镜分析膜受体扩散和簇簇的图像处理协议

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜（FLIM）

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜（FLIM）

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

摘要

探索更多视频

单分子跟踪显微镜 - 确定细胞分子扩散状态的工具

可视化单分子络合物在体内使用高级荧光显微

点变异荧光相关光谱用于分析活细胞质膜上的分子扩散

由荧光相关光谱测量的一次淋巴细胞的细胞膜分子扩散

荧光寿命成像显微镜观察细胞内圈套的贩运

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）

测绘在细胞膜分子扩散，多目标跟踪（MTT）

用荧光显微镜分析膜受体扩散和簇簇的图像处理协议

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜 （FLIM）

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜 （FLIM）

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜（FLIM）

多细胞球体的生产和多参数活细胞荧光寿命成像显微镜（FLIM）