这项工作是由Lundbeck公司初级组组长奖学金到LNN支持。 PWW承认从加拿大自然科学和工程研究理事会（NSERC）补助资金支持。我们也感谢丹麦分子生物成像中心南丹麦大学访问旋转盘显微镜。

采集在质膜EGFP-标记的蛋白的KICS分析可以在落射荧光显微镜，TIRF设置或在一个旋转盘显微镜设置为获取所关注的膜的图像来完成。摄像机像素尺寸以及图像帧之间的时间是需要的分析。可用于分析在4-30赫兹帧频100-1,200帧的图像序列。在采集时，要保持对焦的膜在整个成像持续时间和集中于平膜，其中，荧光均匀分布的一小部分是很重要的。移动囊泡，突出膜区域和细胞器可以稍后在分析过程中裁剪出。采集时间的选择应使得存在的细胞的无漂移或运动。 要获得KICS代码脚本的MATLAB，请联系保罗·怀斯曼（Paul.Wiseman @ McGill.ca）。第一次KICS代码时，打开MAT劳顾会，并单击文件，然后设置路径，然后单击添加子文件夹，并在其中找到了KICS代码所在的计算机上的文件夹。然后点击确定，保存并关闭。现在，继续在未来的点描述作物的分析。 1，导入利息的图像序列到成像分析程序为TIFF堆栈与保存的文件名称：stack1.tif。 <ol><li>在膜不包括运动细胞器和膜突出区域的平坦部分选择的感兴趣区（ROI）的矩形区域。裁切尺寸选择，使那些好的K 2地块产生了足够的统计数据。 </li><li>裁剪区域并保存作物在适当的文件夹中的TIFF文件。如果有多个庄稼从同一影片，使用数增加量， 例如 “stack1crop.tif”，“stack1crop2.tif”，“stack1crop3.tif”。 </li><li>将包含本地作物的文件夹在电脑上，而不是在服务器上，而这样做KICS分析。 </li></ol> 2，导入作物进入分析软件逐一进行分析<ol><li>在命令窗口，然后按打开MATLAB和类型“icsgui”ENTER。 ICS的界面是针对图像相关光谱图形用户界面程序的可执行文件名。 </li><li>在ICS界面点击“KICS”选项卡。屏幕截图的分析窗口如图1。 </li><li>找到文件夹名称“MATLAB代码”的文件夹，然后滚动到文件，文件名为“脚本”，并双击它打开此。或者，右键单击该文件，选择“打开用MATLAB”，或转到文件，在MATLAB中打开并打开脚本文件。此文件被称为编辑器。 </li><li>在编辑器中滚动到“加载KICS数据集”，然后复制或键入文件名和文件夹位置到命令行的开始与IMG = 例如 “C：用户文档 AQP3dynamics stack1crop.tif”。在下面的文件夹位置在命令行中设置帧进行分析的号码- 如：[1:500]。使用相同的设置适用于所有连续的电影中的数据系列。如果有焦点漂移在以后的框架，这些都应该被排除在分析之外。 </li><li>在编辑器中单击“保存”，然后点击“计算单元”。该数据集现在被装载到到分析软件。 </li><li>在GUI中KICS分析窗口中，输入分析的设置： <ol><li>不要选取“T细胞”框。 </li><li>输入的时间滞后数进行分析。的时间延迟（τ）的数量将有作用，对扩散情节，必须选择这样的扩散图是线性的。开始输入25，然后下降到扩散剧情是线性的。 τ是多少时间滞后于KICS分析比较和一个时间滞后的时刻Between一帧和下一。最小的值，给出了一个线性图应该被选中。时间的最大数量滞后选择这样的线性拟合得到，选择较高的值会产生不能被线拟合数据。 </li><li>输入最大的 K 2的值（见圆圈1在图1中），它通常是20-50。一个好的K 2图是一个阴谋，其中有些是沿直线分布的许多数据点。从输入70，然后在评估的K 2和扩散曲线后下降，并选择最低的值，其中围绕一条直线上的数据点簇。第k 2的值是空的k-矢量在傅立叶空间中的平方幅度。 最初，分析重复，应直到最好的值被确定，然后使用相同的设置适用于所有连续的电影中的数据系列，但请务必检查所选择的设置提供一个良好的适合的数据：好K 2地块和线性扩散的情节。 </li><li>点击“保存设置并继续”。 </li><li>点击“是”，显示所有的图形。 </li><li>点击“载入图像系列”（见圈2 图1），然后单击“工作空间”。 </li><li>选择“imgSerCrop”，然后单击“从工作区”。 </li><li>进入成像系统采集设置。在框“像素大小”中输入的预测像素大小为在该图像栈获得的成像系统。为AQP3-EGFP 0.111使用。在方块“帧之间输入时间（s）”，0.1150用于水通道蛋白3-EGFP。 </li><li>单击“选择感兴趣区”，输入“1”，点击确定，“使用整个图像”。 </li><li>单击“做KICS分析”，然后单击是做“动过滤”。结果将作为图像自动打开。 </li><li>最小化的设置窗口，尽量减少电池信息windo的w和最小化的光物理窗口。在动力学窗口，检查动力学曲线显示的数据，以具有负斜率意味着该数据点相关，并自由扩散可以假设的直线的线性拟合。记录中的扩散系数的特定的时间滞后和k 2的设置（这是没有必要留意拟合的标准偏差）。在K图2中的数据点必须围绕线被聚集在指定的时间滞后。 </li><li>勾选框“另存开放数字图像”，然后单击“保存打开的数字图像”保存结果文件。保存在C一个新的文件夹：用户文档 AQP3diffusion。点击“清除当前数据”，然后继续下榨季的分析。 </li></ol></li></ol> 3，平均的计算扩散系数的计算方式来获取分析数据的概述<ol><li>从一个SPRE每个ROI输入个人扩散系数adsheet（一定要注意τ和K 2的值），使用作物如上面设定的名称。 </li><li>使用电子表格程序计算平均扩散系数和标准偏差。 </li><li>执行Kolmogorov-Smirnov检验或学生t检验用5％的显着性水平来评估统计学差异。细胞（例如处理与未处理）之间Quantitave可以用比较的。 </li><li>打开这是由分析软件产生用于每个作物和平均数据为每个条件的每个时间间隔的扩散曲线的电子表格的版本。产生一个新的平均扩散阴谋在提交论文或演讲。 </li></ol>

<ol>
	<li>Kolin, D. L., Ronis, D., 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=k-Space+image+correlation+spectroscopy:+A+method+for+accurate+transport+measurements+independent+of+fluorophore+photophysics.">k-Space image correlation spectroscopy: A method for accurate transport measurements independent of fluorophore photophysics.</a> Biophysical Journal. 91, 3061-3075 (2006).</li><li>Saxton, M. J., Jacobson, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-particle+tracking:+Applications+to+membrane+dynamics.">Single-particle tracking: Applications to membrane dynamics.</a> Annual Review of Biophysics and Biomolecular Structure. 26, 373-399 (1997).</li><li>Bannai, H., Levi, S., Schweizer, C., Dahan, M., Triller, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+the+lateral+diffusion+of+membrane+molecules+with+quantum+dots.">Imaging the lateral diffusion of membrane molecules with quantum dots.</a> Nat Protoc. 1, 2628-2634 (2006).</li><li>Jaqaman, 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=Robust+single-particle+tracking+in+live-cell+time-lapse+sequences.">Robust single-particle tracking in live-cell time-lapse sequences.</a> Nat Methods. 5, 695-702 (2008).</li><li>Pinaud, F., 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=Dynamic+partitioning+of+a+glycosyl-phosphatidylinositol-anchored+protein+in+glycosphingolipid-rich+microdomains+imaged+by+single-quantum+dot+tracking.">Dynamic partitioning of a glycosyl-phosphatidylinositol-anchored protein in glycosphingolipid-rich microdomains imaged by single-quantum dot tracking.</a> Traffic. 10, 691-712 (2009).</li><li>Wieser, S., Axmann, M., Schutz, G. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Versatile+analysis+of+single-molecule+tracking+data+by+comprehensive+testing+against+Monte+Carlo+simulations.">Versatile analysis of single-molecule tracking data by comprehensive testing against Monte Carlo simulations.</a> Biophys J. 95, 5988-6001 (2008).</li><li>Sbalzarini, I. F., Koumoutsakos, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Feature+point+tracking+and+trajectory+analysis+for+video+imaging+in+cell+biology.">Feature point tracking and trajectory analysis for video imaging in cell biology.</a> Journal of Structural Biology. 151, 182-195 (2005).</li><li>Durisic, N., 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=Detection+and+correction+of+blinking+bias+in+image+correlation+transport+measurements+of+quantum+dot+tagged+macromolecules.">Detection and correction of blinking bias in image correlation transport measurements of quantum dot tagged macromolecules.</a> Biophys J. 93, 1338-1346 (2007).</li><li>Umenishi, F., Verbavatz, J. M., Verkman, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=cAMP+regulated+membrane+diffusion+of+a+green+fluorescent+protein-aquaporin+2+chimera.">cAMP regulated membrane diffusion of a green fluorescent protein-aquaporin 2 chimera.</a> Biophys J. 78, 1024-1035 (2000).</li><li>Levin, M. H., Haggie, P. M., Vetrivel, L., Verkman, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+in+the+endoplasmic+reticulum+of+an+aquaporin-2+mutant+causing+human+nephrogenic+diabetes+insipidus.">Diffusion in the endoplasmic reticulum of an aquaporin-2 mutant causing human nephrogenic diabetes insipidus.</a> The Journal of biological chemistry. 276, 21331-21336 (2001).</li><li>Semrau, S., Schmidt, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Particle+image+correlation+spectroscopy+(PICS):+retrieving+nanometer-scale+correlations+from+high-density+single-molecule+position+data.">Particle image correlation spectroscopy (PICS): retrieving nanometer-scale correlations from high-density single-molecule position data.</a> Biophys J. 92, 613-621 (2007).</li><li>Petersen, N. O., Hoddelius, P. L., Wiseman, P. W., Seger, O., Magnusson, K. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitation+of+membrane+receptor+distributions+by+image+correlation+spectroscopy:+concept+and+application.">Quantitation of membrane receptor distributions by image correlation spectroscopy: concept and application.</a> Biophys J. 65, 1135-1146 (1993).</li><li>Marlar, S., Arnspang, E. C., Koffman, J. S., L&#248;cke, E. M., Christensen, B. M., Nejsum, L. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Elevated+cAMP+increases+aquaporin-3+plasma+membrane+diffusion.">Elevated cAMP increases aquaporin-3 plasma membrane diffusion.</a> Am J Physiol Cell Physiol. 306, (2014).</li></ol>

作者宣称，他们有没有竞争的财务权益。

本文介绍了如何应用KICS分析方法，从蛋白质标记荧光蛋白的显微镜图像确定扩散系数的详细一步一步的概述。该分析是独立探针的选择与标记密度非常广阔的动态范围，并且可以由此也可以应用到标记的量子点以及染料和荧光蛋白，例如绿色荧光蛋白的蛋白质。 计算该蛋白质的有效扩散系数，有几个关键步骤，这已经得到了优化。至关重要的是仅在膜图像标记的蛋白质。如?...

质膜蛋白质的四维时空组织和横向流动被严格调控，并可能在蛋白质的功能，活性和蛋白质 - 蛋白质相互作用中发挥作用。质膜蛋白的侧向扩散，在传统上被研究通过计算单个微粒的扩散系数由量子点的时间推移成像或染料标记的质膜蛋白2-4。这种方法需要插入质膜中的蛋白质对量子点或染料标记，它可以破坏蛋白质折叠和功能，因此，不能达到对某些蛋白质的胞外标记。量子点的空间体积已经显示出减缓蛋白5的扩散，而且，在人口中的蛋白质只有一小部分被标以量子点，并且如果该馏分是代表对总它不知道池质膜蛋白。单粒子TRA扩散系数从形象系列量子点标记的蛋白他妈的（SPT）的测量涉及的映射与二维高斯粒子的适应其次是广泛的分析算法成像的峰位。该分析在计算上是非常密集的，需要大量的非线性曲线拟合中的时间推移序列的每个图像帧的显微镜点扩散函数（通常为2维空间高斯）和粒子位置的后续联的近似成粒子轨迹描述单分子6,7的运动。 一项最近开发的图像相关技术，K空间图像相关光谱（KICS）使扩散系数的相对简单的测量的荧光标记质膜蛋白。经常性地计算由KICS标有荧光蛋白膜蛋白的扩散系数的可能性是它拥有独特的工具比传统的量子几个优点点SPT分析：外标签和费时外标签无插入是必需的（可用于表达荧光蛋白的细胞系）;扩散系数是从比较标记的量子点的子集的荧光蛋白的总萃取池;分析是简单而不需要跟踪单个蛋白质和分析，可以使用具有附加的用户编程不要求现有的代码来执行。该方法快速，因为它是一个平均的技术，它能够快速计算扩散系数和计算。这些快速扩散测量的蛋白质补充人口的艰苦SPT方法获得的总体的子集的更详细的分子运输信息。 KICS相关时间已先被转化为傅立叶空间荧光显微图像序列，从而分离FL由于从那些由于分子运输1光物理uorescence波动。其结果是，KICS可以确定数密度，流动速度和扩散的荧光而被中立通过复杂的光漂白或闪烁的荧光团标记的分子。这使得KICS用于快速确定荧光标记的细胞的膜蛋白的扩散动力学，而不需要自定义写入算法的有用工具。除了 ​​荧光标记的蛋白，KICS也可以应用到量子点标记的膜蛋白8。 本文提供了一步一步的介绍如何使用KICS演示了如何将作物，如何使用代码，以及如何评估产生的地块，提取绿色荧光蛋白标记的质膜蛋白质的扩散系数从中扩散系数进行萃取。作为一个例子，通过旋转圆盘镜组中半全内反射所获得的数据发荧光NCE（TIRF）模式标记EGFP肾水通道蛋白水通道蛋白3（AQP3）中，提出了。

<table border="0" cellpadding="0" cellspacing="0" width="406">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DMEM</td>
			<td style="width:71px;">Gibco</td>
			<td style="width:119px;">31600-083</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">FBS</td>
			<td style="width:71px;">Invitrogen</td>
			<td>10082147</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Penicilin&#160;&#160;</td>
			<td style="width:71px;">Sigma</td>
			<td><a href="http://www.sigmaaldrich.com/catalog/product/sigma/13752?lang=en&amp;region=DK">13752</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Kanamycin</td>
			<td style="width:71px;">Gibco</td>
			<td>15160070</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Streptomycin</td>
			<td style="width:71px;">Gibco</td>
			<td>11860038</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Phenol red free medium</td>
			<td style="width:71px;">Gibco</td>
			<td>11880-028</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DMSO</td>
			<td style="width:71px;">Sigma</td>
			<td><a href="http://www.sigmaaldrich.com/catalog/product/sigma/d8418?lang=en&amp;region=DK">D8418&#160;</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HEPES</td>
			<td style="width:71px;">Gibco</td>
			<td>15630056</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Apparatus</td>
			<td style="width:71px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Spinning Disk Microscope</td>
			<td style="width:71px;">Nikon</td>
			<td style="width:119px;">Ti Eclipse</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">EMCCD Camera</td>
			<td style="width:71px;">Andor</td>
			<td style="width:119px;">Ixon+</td>
		</tr>
	</tbody>
</table>

easy measurement of diffusion coefficients of egfp-tagged plasma membrane proteins using k-space image correlation spectroscopy

横向扩散和质膜蛋白的条块被严格调控的细胞，因此，研究这些过程，就会发现新的见解到质膜蛋白的功能和调节。最近，K空间图像相关光谱（KICS）1的开发，使扩散系数的常规测量直接从荧光标记细胞膜蛋白的图像，即避免探头光物理引入系统偏差。虽然用于分析的理论基础是复杂的，该方法可以通过使用一个免费提供的代码来测量蛋白质的扩散系数非专家来实现。 KICS计算时间相关函数从荧光显微图像堆栈的每个图像的傅立叶变换倒数（K-）空间后。随后，圆形平均，自然对数变换和线性拟合的相关函数产生的扩散系数。这本文提供了一步一步的指导，通过KICS图像分析和扩散系数的测量。 首先，使用荧光显微镜获取荧光标记的细胞质膜蛋白质的高帧频的图像序列。然后，感兴趣区域（ROI）避免细胞内细胞器，移动囊泡或凸膜区域的区域被选中。投资回报率堆栈被导入到一​​个可以自由使用的代码和几个定义的参数（见方法部分）是为KICS分析设置。然后程序会生成一个情节从k空间时间相关函数“的坡坡”，而扩散系数是从该曲线的斜率计算。下面是一步一步的KICS程序使用肾水通道蛋白-3标有绿色荧光蛋白作为一个典型的例子来衡量一个膜蛋白的扩散系数。

为了获得合适的图像栈与KICS进行分析，不同的显微镜系统都可以使用。因此能够分析来自一个落射荧光显微镜，以及一个TIRF或旋转盘设置图像序列。该膜必须是平的，没有任何大的运动细胞器或移动囊泡/对象。本文提出AQP3的具有标记的EGFP在成象在一个旋转盘显微镜的焦点设定到质膜在9.2赫兹帧频活MDCK细胞一缩时图像序列。的焦点被设置在基底（底）质膜。该数据已出版的AJP细胞13。 </...

Watch this Scientific Journal Video about Easy Measurement of Diffusion Coefficients of EGFP-tagged Plasma Membrane Proteins Using k-Space Image Correlation Spectroscopy at JoVE.com

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

本文提供了一个一步一步引导到波动分析技术K空间图像相关光谱（KICS），用于测量扩散系数的荧光在活的哺乳动物细胞标记质膜蛋白。

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 ...

easy-measurement-diffusion-coefficients-egfp-tagged-plasma-membrane

Research

JoVE Journal

Biology

10.6K 次观看.  Aarhus University. 本文提供了一个一步一步引导到波动分析技术K空间图像相关光谱（KICS），用于测量扩散系数的荧光在活的哺乳动物细胞标记质膜蛋白。 

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

Measuring Diffusion Coefficients via Two-photon Fluorescence Recovery After Photobleaching

Multi-fluorescence recovery after photobleaching is a microscopy technique used to measure the diffusion coefficient (or analogous transport parameters) of macromolecules, and can be applied to both in vitro and in vivo biological systems. Multi-fluorescence recovery after photobleaching is performed by photobleaching a region of interest within a fluorescent sample using an intense laser flash, then attenuating the beam and monitoring the fluorescence as still-fluorescent molecules from outside the region of interest diffuse in to replace the photobleached molecules. We will begin our demonstration by aligning the laser beam through the Pockels Cell (laser modulator) and along the optical path through the laser scan box and objective lens to the sample. For simplicity, we will use a sample of aqueous fluorescent dye. We will then determine the proper experimental parameters for our sample including, monitor and bleaching powers, bleach duration, bin widths (for photon counting), and fluorescence recovery time. Next, we will describe the procedure for taking recovery curves, a process that can be largely automated via LabVIEW (National Instruments, Austin, TX) for enhanced throughput. Finally, the diffusion coefficient is determined by fitting the recovery data to the appropriate mathematical model using a least-squares fitting algorithm, readily programmable using software such as MATLAB (The Mathworks, Natick, MA).

In this article we will describe the procedure for measuring diffusion coefficients using multi-photon fluorescence recovery after photobleaching. We will begin by aligning the laser along the optical path to the sample and determining the proper experimental parameters, then continue generating and finally fitting fluorescence recovery curves.

通过双光子荧光恢复漂白后测量扩散系数

Multi-fluorescence recovery after photobleaching is a microscopy technique used to measure the diffusion coefficient (or analogous transport parameters) ...

科研

生物学

Crystallizing Membrane Proteins for Structure Determination using Lipidic Mesophases

A detailed protocol for crystallizing membrane proteins by using lipidic mesophases is described. This method has variously been referred to as the lipidic cubic phase or in meso method. The method has been shown to be quite versatile in that it has been used to solve X-ray crystallographic structures of prokaryotic and eukaryotic proteins, proteins that are monomeric, homo- and hetero-multimeric, chromophore-containing and chromophore-free, and alpha-helical and beta-barrel proteins. Recent successes using in meso crystallization are the human engineered beta2-adrenergic and adenosine A2a G protein-coupled receptors. Protocols are presented for reconstituting the membrane protein into the monoolein-based mesophase, and for setting up crystallizations in the manual mode. Additional steps in the overall process, such as crystal harvesting, are to be addressed in future video articles. The time required to prepare the protein-loaded mesophase and to set up a crystallization plate manually is about one hour.

Herein is described the procedure implemented in the Caffrey Membrane Structural and Functional Biology Group to set up manually crystallization trials of membrane proteins in lipidic mesophases.

使用油脂介孔结构的测定结晶膜蛋白

A detailed protocol for crystallizing membrane proteins by using lipidic mesophases is described. This method has variously been referred to as the ...

Quantitative Measurement of GLUT4 Translocation to the Plasma Membrane by Flow Cytometry

Glucose is the main source of energy for the body, requiring constant regulation of its blood concentration. Insulin release by the pancreas induces glucose uptake by insulin-sensitive tissues, most notably the brain, skeletal muscle, and adipocytes. Patients suffering from type-2 diabetes and/or obesity often develop insulin resistance and are unable to control their glucose homeostasis. New insights into the mechanisms of insulin resistance may provide new treatment strategies for type-2 diabetes.
The GLUT family of glucose transporters consists of thirteen members distributed on different tissues throughout the body1. Glucose transporter type 4 (GLUT4) is the major transporter that mediates glucose uptake by insulin sensitive tissues, such as the skeletal muscle. Upon binding of insulin to its receptor, vesicles containing GLUT4 translocate from the cytoplasm to the plasma membrane, inducing glucose uptake. Reduced GLUT4 translocation is one of the causes of insulin resistance in type-2 diabetes2,3.
The translocation of GLUT4 from the cytoplasm to the plasma membrane can be visualized by immunocytochemistry, using fluorophore-conjugated GLUT4-specific antibodies.
Here, we describe a technique to quantify total amounts of GLUT4 translocation to the plasma membrane of cells during a chosen duration, using flow cytometry. This protocol is rapid (less than 4 hours, including incubation with insulin) and allows the analysis of as few as 3,000 cells or as many as 1 million cells per condition in a single experiment. It relies on anti-GLUT4 antibodies directed to an external epitope of the transporter that bind to it as soon as it is exposed to the extracellular medium after translocation to the plasma membrane.

This protocol describes a rapid technique to quantify the translocation of GLUT4 from the cytoplasm to the plasma membrane of cells by flow cytometry.

流式细胞仪定量测定GLUT4转位到质膜

Glucose is the main source of energy for the body, requiring constant regulation of its blood concentration. Insulin release by the pancreas induces ...

Crystallization of Membrane Proteins in Lipidic Mesophases

Membrane proteins perform critical functions in living cells related to signal transduction, transport and energy transformations, and, as such, are implicated in a multitude of malfunctions and diseases. However, a structural and functional understanding of membrane proteins is strongly lagging behind that of their soluble partners, mainly, due to difficulties associated with their solubilization and generation of diffraction quality crystals. Crystallization in lipidic mesophases (also known as in meso or LCP crystallization) is a promising technique which was successfully applied to obtain high resolution structures of microbial rhodopsins, photosynthetic proteins, outer membrane beta barrels and G protein-coupled receptors. In meso crystallization takes advantage of a native-like membrane environment and typically produces crystals with lower solvent content and better ordering as compared to traditional crystallization from detergent solutions. The method is not difficult, but requires an understanding of lipid phase behavior and practice in handling viscous mesophase materials. Here we demonstrate a simple and efficient way of making LCP and reconstituting a membrane protein in the lipid bilayer of LCP using a syringe mixer, followed by dispensing nanoliter portions of LCP into an assay or crystallization plate, conducting pre-crystallization assays and harvesting crystals from the LCP matrix. These protocols provide a basic guide for approaching in meso crystallization trials; however, as with any crystallization experiment, extensive screening and optimization are required, and a successful outcome is not necessarily guaranteed.

The protocols describe the essential steps for obtaining diffraction quality crystals of a membrane protein starting from reconstitution of the protein in a lipidic cubic phase (LCP), finding initial conditions with LCP-FRAP pre-crystallization assays, setting up LCP crystallization trials and harvesting crystals.

在油脂介孔膜蛋白的结晶

Membrane proteins perform critical functions in living cells related to signal transduction, transport and energy transformations, and, as such, are ...

Quantification of Proteins Using Peptide Immunoaffinity Enrichment Coupled with Mass Spectrometry

There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in quantitation, are associated with a high cost, long lead time, and are fraught with drawbacks (e.g. heterophilic antibodies, autoantibody interference, 'hook-effect').1 An alternative technique is affinity enrichment of peptides coupled with quantitative mass spectrometry, commonly referred to as SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies).2 In this technique, affinity enrichment of peptides with stable isotope dilution and detection by selected/multiple reaction monitoring mass spectrometry (SRM/MRM-MS) provides quantitative measurement of peptides as surrogates for their respective proteins. SRM/MRM-MS is well established for accurate quantitation of small molecules 3, 4 and more recently has been adapted to measure the concentrations of proteins in plasma and cell lysates.5-7 To achieve quantitation of proteins, these larger molecules are digested to component peptides using an enzyme such as trypsin. One or more selected peptides whose sequence is unique to the target protein in that species (i.e. "proteotypic" peptides) are then enriched from the sample using anti-peptide antibodies and measured as quantitative stoichiometric surrogates for protein concentration in the sample. Hence, coupled to stable isotope dilution (SID) methods (i.e. a spiked-in stable isotope labeled peptide standard), SRM/MRM can be used to measure concentrations of proteotypic peptides as surrogates for quantification of proteins in complex biological matrices. The assays have several advantages compared to traditional immunoassays. The reagents are relatively less expensive to generate, the specificity for the analyte is excellent, the assays can be highly multiplexed, enrichment can be performed from neat plasma (no depletion required), and the technique is amenable to a wide array of proteins or modifications of interest.8-13 In this video we demonstrate the basic protocol as adapted to a magnetic bead platform.

Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) couples affinity enrichment of peptides with stable isotope dilution mass spectrometry (MRM-MS) to provide quantitative measurement of peptides as surrogates for their respective proteins. Here we describe the protocol using magnetic particles in a partially automated format.

加上质谱肽免疫亲和富集的蛋白质定量

There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in ...

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 ...

Use of a Robot for High-throughput Crystallization of Membrane Proteins in Lipidic Mesophases

Structure-function studies of membrane proteins greatly benefit from having available high-resolution 3-D structures of the type provided through macromolecular X-ray crystallography (MX). An essential ingredient of MX is a steady supply of ideally diffraction-quality crystals. The in meso or lipidic cubic phase (LCP) method for crystallizing membrane proteins is one of several methods available for crystallizing membrane proteins. It makes use of a bicontinuous mesophase in which to grow crystals. As a method, it has had some spectacular successes of late and has attracted much attention with many research groups now interested in using it. One of the challenges associated with the method is that the hosting mesophase is extremely viscous and sticky, reminiscent of a thick toothpaste. Thus, dispensing it manually in a reproducible manner in small volumes into crystallization wells requires skill, patience and a steady hand. A protocol for doing just that was developed in the Membrane Structural &amp; Functional Biology (MS&amp;FB) Group1-3. JoVE video articles describing the method are available1,4. 
The manual approach for setting up in meso trials has distinct advantages with specialty applications, such as crystal optimization and derivatization. It does however suffer from being a low throughput method. Here, we demonstrate a protocol for performing in meso crystallization trials robotically. A robot offers the advantages of speed, accuracy, precision, miniaturization and being able to work continuously for extended periods under what could be regarded as hostile conditions such as in the dark, in a reducing atmosphere or at low or high temperatures. An in meso robot, when used properly, can greatly improve the productivity of membrane protein structure and function research by facilitating crystallization which is one of the slow steps in the overall structure determination pipeline. 
In this video article, we demonstrate the use of three commercially available robots that can dispense the viscous and sticky mesophase integral to in meso crystallogenesis. The first robot was developed in the MS&amp;FB Group5,6. The other two have recently become available and are included here for completeness.	
An overview of the protocol covered in this article is presented in Figure 1. All manipulations were performed at room temperature (~20 &deg;C) under ambient conditions.

Herein is described a robotic approach to high-throughput crystallization of membrane proteins in lipidic mesophases for use in structure determination using macromolecular X-ray crystallography. Three robots capable of handling the viscous and sticky protein-laden mesophase integral to the method are introduced.

使用机器人在油脂中间相高通量膜蛋白的结晶

Structure-function studies of membrane proteins greatly benefit from having available high-resolution 3-D structures of the type provided through ...

The Cell-based L-Glutathione Protection Assays to Study Endocytosis and Recycling of Plasma Membrane Proteins

Membrane trafficking involves transport of proteins from the plasma membrane to the cell interior (i.e. endocytosis) followed by trafficking to lysosomes for degradation or to the plasma membrane for recycling. The cell based L-glutathione protection assays can be used to study endocytosis and recycling of protein receptors, channels, transporters, and adhesion molecules localized at the cell surface. The endocytic assay requires labeling of cell surface proteins with a cell membrane impermeable biotin containing a disulfide bond and the N-hydroxysuccinimide (NHS) ester at 4 &#186;C -&#160;a temperature at which membrane trafficking does not occur. Endocytosis of biotinylated plasma membrane proteins is induced by incubation at 37 &#186;C. Next, the temperature is decreased again to 4 &#186;C to stop endocytic trafficking and the disulfide bond in biotin covalently attached to proteins that have remained at the plasma membrane is reduced with L-glutathione. At this point, only proteins that were endocytosed remain protected from L-glutathione and thus remain biotinylated. After cell lysis, biotinylated proteins are isolated with streptavidin agarose, eluted from agarose, and the biotinylated protein of interest is detected by western blotting. During the recycling assay, after biotinylation cells are incubated at 37 &#176;C to load endocytic vesicles with biotinylated proteins and the disulfide bond in biotin covalently attached to proteins remaining at the plasma membrane is reduced with L-glutathione at 4 &#186;C as in the endocytic assay. Next, cells are incubated again at 37 &#176;C to allow biotinylated proteins from endocytic vesicles to recycle to the plasma membrane. Cells are then incubated at 4 &#186;C, and the disulfide bond in biotin attached to proteins that recycled to the plasma membranes is reduced with L-glutathione. The biotinylated proteins protected from L-glutathione are those that did not recycle to the plasma membrane.

Membrane trafficking involves transport of proteins from the plasma membrane to the cell interior (i.e. endocytosis) followed by trafficking to lysosomes for degradation or to the plasma membrane for recycling. Methods described in this article are designed to study endocytosis and recycling of plasma membrane proteins.

Membrane trafficking involves transport of proteins from the plasma membrane to the cell interior (i.e. endocytosis) followed by trafficking to lysosomes ...

Imaging Plasma Membrane Deformations With pTIRFM

To gain novel insights into the dynamics of exocytosis, our group focuses on the changes in lipid bilayer shape that must be precisely regulated during the fusion of vesicle and plasma membranes. These rapid and localized changes are achieved by dynamic interactions between lipids and specialized proteins that control membrane curvature. The absence of such interactions would not only have devastating consequences for vesicle fusion, but a host of other cellular functions that involve control of membrane shape. In recent years, the identity of a number of proteins with membrane-shaping properties has been determined. What remains missing is a roadmap of when, where, and how they act as fusion and content release progress.
Our understanding of the molecular events that enable membrane remodeling has historically been limited by a lack of analytical methods that are sensitive to membrane curvature or have the temporal resolution to track rapid changes. PTIRFM satisfies both of these criteria. We discuss how pTIRFM is implemented to visualize and interpret rapid, submicron changes in the orientation of chromaffin cell membranes during dense core vesicle (DCV) fusion. The chromaffin cells we use are isolated from bovine adrenal glands. The membrane is stained with a lipophilic carbocyanine dye,1,1&#39;-dioctadecyl-3,3,3&#39;,3&#39;-tetramethylindodicarbocyanine, 4-chlorobenzenesulfonate, or&#160;diD. DiD intercalates in the membrane plane with a &#34;fixed&#34; orientation and is therefore sensitive to the polarization of the evanescent field. The diD-stained cell membrane is sequentially excited with orthogonal polarizations of a 561&#160;nm laser (p-pol, s-pol). A 488&#160;nm laser is used to visualize vesicle constituents and time the moment of fusion. Exocytosis is triggered by locally perfusing cells with a depolarizing KCl solution. Analysis is performed offline using custom-written software to understand how diD emission intensity changes relate to fusion pore dilation.

Polarization-based Total Internal Reflection Fluorescence Microscopy (pTIRFM) enables real-time detection of cell membrane dynamics. This article describes the implementation of pTIRFM for the study of membrane remodeling during regulated exocytosis. The technique is generalizable to other processes in cell biology that directly or indirectly involve changes in membrane shape.

成像质膜变形随着pTIRFM

To gain novel insights into the dynamics of exocytosis, our group focuses on the changes in lipid bilayer shape that must be precisely regulated during ...

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.

We describe the use of digital image correlation to characterize the local surface strain field on vascular tissue samples subjected to uniaxial tensile testing. These measurements facilitate precise quantification of the sample mechanical response and the generation of constitutive stress-strain relations.

利用数字图像相关表征的血管组织标本本地菌株

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and ...