这项研究得到了日本文部科学省（18K04843）向Y. Yawata，JST ERATO（JPMJER1502）到N. Nomura的科学研究资助的部分支持。

1. 样品的制备
<ol><li>将带有孔的1毫米厚硅胶垫圈放在载玻片上。</li>
	<li>将1毫米厚的0.8%（w / v）琼脂糖板坯放在硅胶垫圈的孔中。</li>
	<li>将任意微生物细胞培养物的细胞密度稀释至600nm（OD660）= 1.0的光密度。</li>
	<li>将5μL等分试样的细胞悬浮液放在琼脂糖板上。</li>
	<li>用玻璃盖板轻轻盖住。</li>
</ol>2. 显微镜的设置
注意:CRIF技术结合了共聚焦反射显微镜（CRM）和多通道共聚焦显微光谱。CRM是细胞形态学和空间定位的信息来源，其独立于细胞先天荧光。多通道共聚焦显微光谱提供细胞先天荧光的光谱信息。在下面的协议中，使用CRM或共聚焦荧光显微光谱学获取的任何图像分别称为CRM图像或多通道共聚焦显微光谱图像。
<ol><li>将具有去扫描光谱通道的共聚焦显微镜连接到光电倍增管（PMT）或GaAsP检测器。 注:这些设置可从多家制造商处获得。</li>
	<li>为显微镜配备具有足够放大倍率的高数值孔径（NA）物镜。 注意:建议使用 NA > 1.4 的 63x 物镜来分析细菌细胞。</li>
	<li>为显微镜配备半反射镜（例如NT 80/20）以适应CRM，CRM依靠入射光的细胞散射来可视化细胞形态。</li>
	<li>对于多通道共聚焦显微光谱，请为显微镜配备二向色镜。例如，将 MBS InVis405、MBS458、MBS488、MBS458/514、MBS488/543 或 MBS 488/543/633 分束器分别用于 405、458、488、514、543 或 633 nm 激发。</li>
	<li>使用激光功率计调整每个激发波长的照明强度。通过激发波长保持显微镜下的输出恒定（例如，使用63x物镜使用50μW）。</li>
</ol>3. 图像采集
<ol><li>使用显微镜软件将针孔尺寸设置为1 AU。</li>
	<li>设置每个激发波长的像素停留时间（即扫描速度）。 注意:过长的像素停留时间会损坏细胞。避免过长的像素停留时间，以最大限度地减少对细胞的光损伤。对于细菌样品，像素停留时间<55.6 μs/μm2 （当显微镜下的辐照度输出为~17 μW/cm2时）通常适合于避免生长抑制。该参数可能因生物体和实验装置而异。</li>
	<li>设置扫描分辨率。对于细菌等小细胞，请使用 1，024 x 1，024 的扫描区域。</li>
	<li>设置 Z 轴扫描范围，以便覆盖感兴趣的区域。 注意:对于分布在琼脂糖板上的细菌和酵母细胞样品，Z扫描范围通常为〜15μm就足够了。</li>
	<li>设置去扫描探测器以捕获可见光波长范围（例如，416−691 nm）。使用8−10 nm的光谱窗口。</li>
	<li>以从最长到最短激发波长的顺序获取多通道共聚焦显微光谱图像，以创建荧光图像的Z层。</li>
	<li>获取 CRM 映像。</li>
	<li>将采集的图像作为 16 位 tiff 文件保存到目录中。使用命名约定 XXXcYYzZZ.tif 命名文件，其中 XXX 是激发波长，YY 是探测器通道数，ZZ 是 Z 切片数，"c"和"z"分别是探测器编号和 Z 切片编号的前缀。<ol>
<li>例如，如果使用激发波长为405nm的多通道共聚焦显微光谱图像，探测器阵列的第 1个探测器通道拍摄，并且是Z-stack的第 5个切片，请将其命名为"405c01z05.tif"。对于 CRM 图像，请使用字符串"CRM"代替 XXX（例如，"CRMc01z05.tif"）。 注: 确定 2D 分割还是 3D 分割最适合图像数据。在小细胞被限制在2D平面（例如，粘附在玻璃表面上的细菌群）的情况下，使用2D分割方法。在细胞群分布在三维空间中（例如，生物膜和组织样品）或细胞大小大于光学切片厚度（例如，酵母细胞，哺乳动物细胞）的情况下，使用3D分割方法。对于2D分割，请参阅第4节;有关 3D 分割，请参阅第 5 节。</li>
	</ol>
</li>
</ol>4. 二维图像分析
<ol><li>为工作站配备图像分析软件（例如 MATLAB）。</li>
	<li>对单细胞先天荧光特征进行细胞分割和重建。<ol>
<li>打开图像分析软件。</li>
		<li>双击并打开提供的脚本之一"Script2D.m"。</li>
		<li>转到 编辑器 选项卡，然后单击 运行。应出现一个文件夹选择窗口。</li>
		<li>选择在步骤 3.8 中创建的目录，然后单击" 打开 "继续。将自动出现一个对话框，提示输入分割参数。 注意:出于测试目的，请选择提供的数据集（"Sample_2D"）。示例数据集以压缩文件的形式提供，应提前提取。</li>
		<li>输入分割参数: 图像二值化的图像二值化阈值 （0−1） = 0.45， 单元区域阈值上限（以像素为单位） = 200， 单元区域阈值下限（以像素为单位） = 10， 检测器数量 = 32。单击 "确定" 继续。 注:这些参数可能需要根据图像质量进行调整。</li>
		<li>应出现一个显示 CRM 图像的新图像窗口。选择任意背景区域（即单元格不存在的区域）以用于背景减法。通过拖动鼠标在 CRM 图像中绘制一个矩形。在所选区域内双击以确认选择。</li>
		<li>在步骤 4.2.4 中选择的同一目录中查找名为 Signature 的新目录。 注意:提供的代码会自动创建此目录。"Signature"目录将群体中每个微生物细胞的先天荧光特征存储为.png文件，这些文件在通用前缀"Signature"之后按顺序编号。</li>
	</ol>
</li>
</ol>5.3D 图像分析
<ol><li>为工作站配备图像分析软件（材料表）。</li>
	<li>对单细胞先天荧光特征进行细胞分割和重建。<ol>
<li>打开图像分析软件。</li>
		<li>双击并打开提供的脚本"Script3D.m"。</li>
		<li>转到 编辑器 选项卡，然后单击 运行。应出现一个文件夹选择窗口。</li>
		<li>选择在步骤 3.8 中创建的目录，然后单击" 打开 "继续。将自动出现一个对话框，提示输入分割参数。 注意:出于测试目的，请选择提供的数据集（"Sample_3D"）。示例数据集以压缩文件的形式提供，应提前提取。</li>
		<li>输入分割参数: 图像二值化的图像二值化阈值 （0–1） = 0.01， 像元体积阈值（以像素为单位） = 1，000， 像元区域下限阈值（以像素为单位） = 20， X 像素大小 [μm/像素] = 0.26， Y 像素大小 [μm/像素] = 0.26， Z 像素大小 [μm/像素] = 0.42， 检测器数量 = 32。点击 确定 继续;将出现一个对话框，提示输入激发波长的数量。 注:这些参数可能需要根据图像质量进行调整。</li>
		<li>输入用于图像采集的波长数（例如，如果使用405、488、561、630，则在对话框中输入 4 ）。单击" 确定"。</li>
		<li>在对话框中按从最短波长（即框名称: 激发 1 号）到最长波长的顺序输入激发波长。点击 确定 继续;应该会弹出一个显示CRM图像的新图像窗口。</li>
		<li>选择要用于背景减法的任意背景区域（即单元格不存在的区域）。通过拖动鼠标在 CRM 图像中绘制一个矩形。在所选区域内双击以确认选择。</li>
		<li>在步骤 5.2.4 中选择的目录中找到名为 Signature 的目录。 注意:提供的代码会自动创建此目录。"Signature"目录将群体中每个单个微生物细胞的先天荧光特征存储为.png文件，这些文件在通用前缀"Signature"之后按顺序编号。</li>
	</ol>
</li>
</ol>6. 统计分析
注意:执行降维技术（例如，主成分分析[PCA]）以可视化细胞群高光谱的分布。提供的脚本（PCA.py）为两个细胞群（即两个类）执行PCA。
<ol><li>为工作站配备编程语言以及随附的库和模块（材料表）。</li>
	<li>在C驱动器（或等效驱动器）中创建一个空目录，并将该目录命名为"Parent_directory"（即C:/Parent_目录）。</li>
	<li>将两个细胞群中每个细胞群的荧光特征（例如，在步骤4.2.7中生成的.png文件）存储到两个单独的目录中。 注意:这两个目录应都位于"Parent_directory"中。 C:/Parent_directory/ <img alt="image 12" class="xfigimg" src="/files/ftp_upload/61120/61120img1.jpg">普蒂达KT2440/ <img alt="image 13" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 9" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">签名01.png <img alt="image 14" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 10" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">签名02.png <img alt="image 4" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 11" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">: <img alt="image 5" class="xfigimg" src="/files/ftp_upload/61120/61120img1.jpg">普蒂达KT2442/ 
	 <img alt="image 6" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">签名01.png 
	 <img alt="image 7" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">签名02.png 
	 <img alt="image 8" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">:</li>
	<li>将 PCA.py 下载到"Parent_directory"中。</li>
	<li>打开工作站的命令行界面。</li>
	<li>在命令行界面中键入"python C:/Parent_directory/PCA.py"。</li>
	<li>在显示消息"选择目标目录"后选择"Parent_directory"。</li>
	<li>在"C:/Parent_directory"中，找到"PCA.png"，其中包含生成的 PCA 图。</li>
</ol>

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作者没有什么可透露的。

该方法中有两个关键点需要密切关注以获得可重复的结果:1）通过激发波长和实验保持显微镜物镜下的激光功率输出一致，以及2）执行准确的细胞分割。
在比较不同实验之间的先天荧光特征时，第一点尤其重要。避免简单地将相同的"百分比输出"设置应用于激发波长（即，对所有405、488、514和530 nm激光线使用5%功率输出），因为激光线之间的最大功率输出差异可达一个数量级。此外，物镜和内部光学通常具有不均匀的光学吸收特性，这也需要考虑在内。出于这些原因，建议使用激光功率计（材料表）实际测量物镜下的输出。还建议每隔几次实验或定期进行这种测量，因为激光线的输出会在几年内显着衰减。
第二点，准确的细胞分割，在关注种内或种间变异性的情况下变得尤为重要。不准确的细胞分割（图1D）导致异常值数据点（图1E，由红色三角形表示）和更大的明显种内变异性。在进行任何进一步的分析或训练机器学习模型之前，应仔细确定分割参数，通过将分割结果叠加到原始CRM图像上来检查像元分割的准确性。如果处理质量较差的图像，则可能需要额外的图像处理才能实现准确的分割。使用"高斯滤光片"或"中值滤光片"可以去除颗粒状伪影，并且双边滤镜处理可以抵消任何条纹背景。
对于质量较差的光学元件（例如，非共聚焦级物镜）或检测器灵敏度不足，处理微弱先天荧光特征的检测可能具有挑战性。请注意，使用此处和之前描述的设置11，我们没有遇到任何类型的细胞样品，其先天荧光太微弱而无法重建先天荧光特征。虽然更高的激励发射输出和更长的像素停留时间可用于获得更强的发射信号，但这可能会对电池样品造成损坏。对于微弱的先天荧光是一个问题，一种潜在的解决方案是降低背景信号强度，例如通过将细胞悬浮在缓冲液或合成培养基而不是肉汤中。细胞容器的类型，如玻璃底培养皿和微流体装置，与该技术相容且适用，尽管琼脂糖板用于将细胞保留在这里和先前的研究中15。
共聚焦显微镜方法为贴壁细胞群、生物膜和组织样品提供空间分辨率和原位分析。例如，这种方法的一个潜在权衡是与流式细胞仪相比的最大通量。一组完整的共聚焦扫描通过一组扫描收集几百到一千个先天荧光特征可能需要几分钟的时间。流式细胞仪由于其光学设计而灵敏度较低，但可以潜在地实现高出几个数量级的通量。
由于其复杂性，严格鉴定负责先天荧光特征中特定峰的化合物通常具有挑战性。然而，已经提出许多生物学相关分子，如维生素（例如，黄素腺嘌呤二核苷酸[FAD]），辅酶（例如，烟酰胺腺嘌呤二核苷酸[NADH]）和脂褐素色素可能是细胞中的主要荧光团1，16。例如，FAD的激发最大值在350-450 nm之间，发射峰值约为525 nm16。游离NADH的激发最大值和发射峰分别为340 nm和460 nm，尽管蛋白质结合的NADH的发射光谱不同16，17，18。已知与受压或老化细胞相关的脂质色素具有广泛的激发范围（350-500nm）和发射范围（450-600nm）16，18。
CRM的使用提供了一个独立的信息来源来识别细胞轮廓，因此提供了CRIF的另一个显着优势:从分布在3D空间中的单个细胞中选择性提取荧光信号。这代表了对整个微生物菌落或体培养悬浮液的荧光特性的传统分析向前迈出的一步，后者是来自大量细胞的信号的平均混合物，这些信号被来自培养基成分，分泌的代谢物和细胞外基质的非细胞信号污染。 对单细胞先天荧光特征的分析可以预测完整细胞的生理状态，为解决细胞分布和生理状态的时间发展提供潜在的解决方案。

cell1内的各种生物分子发出自发荧光信号，细胞的先天荧光特征由这些信号的组装组成。这种特征性荧光反映了各种细胞特性以及生理状态的差异。先天荧光的分析是微创的，可以补充传统的，更具侵入性的微生物探针，这些探针会留下从轻度代谢修饰到完全细胞破坏的一系列痕迹。虽然DNA或细胞含量提取2，3，荧光原位杂交4以及将荧光报告基因引入基因组等传统技术可有效确定细胞类型或生理状态，但它们通常需要对细胞进行操作或侵入性标记。
对各种活的和完整的微生物菌落的先天荧光的研究表明，包括散装微生物培养悬浮液5，6，活性污泥7，哺乳动物组织8，9和哺乳动物细胞1，10，先天荧光分析有助于对细胞类型和生理状态进行无标记分析。传统上，先天荧光特征是在群体水平上而不是在单细胞水平上进行分析的，因此需要克隆培养。相比之下，此处描述的食灶性反射显微镜辅助单细胞无光泽分析（CRIF）技术11重建并编目了每个活微生物细胞的先天细胞荧光特征。此外，CRIF可以系统地整理分布在三维（3D）空间中的群体中单个微生物细胞的先天荧光特征。

<table><tbody><tr><td>Agarose</td><td>Wako Chemicals</td><td>312-01193</td><td></td></tr><tr><td>Beam splitters</td><td>Carl Zeiss, Nikon</td><td></td><td>MBSInVis405, MBS458, MBS488, MBS458/514, MBS488/543, or MBS 488/543/633 beam splitters (Carl Zeiss)</td></tr><tr><td>Confocal microscope</td><td>Carl Zeiss, Nikon</td><td></td><td>Model LSM 880 (Carl Zeiss), Model A1R (Nikon)</td></tr><tr><td>Cover slips</td><td>Matsunami Glass</td><td>C024601</td><td></td></tr><tr><td>Glass slides</td><td>Matsunami Glass</td><td>S011120</td><td></td></tr><tr><td>Half-reflection mirror</td><td>Carl Zeiss, Nikon</td><td></td><td>NT80/20</td></tr><tr><td>Laser power meter</td><td>Thorlabs</td><td></td><td>PM400 (power meter console) and S175C (sensor)</td></tr><tr><td>LB Broth</td><td>Nacalai tesque</td><td>20066-95</td><td>For bacteria culture</td></tr><tr><td>Image analysis software</td><td>The MathWorks</td><td></td><td>MATLAB version 2019a or later, Image Processing Toolbox is needed</td></tr><tr><td>Microscope objective</td><td>Carl Zeiss, Nikon</td><td>440762-9904</td><td>e.g. 63x plan Apochomat NA = 1.4 (Carl Zeiss)</td></tr><tr><td>Microscope software</td><td>Carl Zeiss, Nikon</td><td></td><td>ZEN (Carl Zeiss),NIS-elements (Nikon)</td></tr><tr><td>PBS(-)</td><td>Wako Chemicals</td><td>166-23555</td><td></td></tr><tr><td>Programming language</td><td></td><td></td><td>Python and libraries, modules (numpy, scikit-learn, scikit-image, os, glob, matplotlib, tkinter) are rquired to run the supplied PCA script.</td></tr><tr><td>Silicone gasket</td><td>ThermoFisher Scientific</td><td>P24744</td><td></td></tr><tr><td>Workstation</td><td></td><td></td><td>A high-performance workstation with discrete GPUs is recommended.</td></tr><tr><td>Yeast extract-peptone-dextrose (YPD) agar medium</td><td>Sigma-Aldrich</td><td>Y1500-250G</td><td>For yeast culture</td></tr><tr><td>YPD medium</td><td>Sigma-Aldrich</td><td>Y1375-250G</td><td></td></tr></tbody></table>

reconstruction of single-cell innate fluorescence signatures by confocal microscopy

这里描述的是共聚焦反射显微镜辅助的单细胞先天荧光分析（CRIF），这是一种微创方法，用于重建分布在三维（3D）空间中的群体中每个个体活细胞的先天细胞荧光特征。细胞的先天荧光特征是由细胞内各种生物分子发出的荧光信号的集合。先前的研究表明，先天荧光特征反映了各种细胞特性和生理状态的差异，是细胞表征和鉴定的丰富信息来源。传统上，先天荧光特征是在群体水平上进行分析的，需要克隆培养，但不是在单细胞水平上。CRIF特别适用于需要3D分辨率和/或选择性提取单个细胞荧光信号的研究。由于荧光特征是细胞的先天特性，CRIF也适用于完整和单个细胞的类型和/或生理状态的无标记预测。这种方法可能是简化细胞分析的强大工具，其中异质性群体中每个单个细胞的表型可以在显微镜下通过其自发荧光特征直接评估，而无需细胞标记。

图1A显示了细菌细胞的典型单细胞荧光特征，以传统光谱图（顶部）和热图（中间）的形式呈现。图1B显示了叠加在土壤细菌群的原始CRM图像上的精确2D细胞分割的结果（假单胞菌KT2440）12。由此产生的群体先天荧光特征在图1D中以热图的形式呈现。请注意，在成功进行细胞分割后，种群内的变异性相对较小。不准确的细胞分割示例如图1C所示，其叠加到如图1B所示的相同P. putida群体上。不准确的细胞分割对群体先天荧光特征的影响从大量异常值中显而易见（图1E，红色三角形）。与精确细胞分割后获得的紧密簇相比，不准确的细胞分割导致PCA后更松散的簇（图1F）。
通常，尽管种内存在变异性，但不同细胞类型的先天荧光特征形成不同的簇。图2C显示了分类学上接近的菌株对（P. putida菌株KT2440和菌株KT244213）的PCA分析结果。尽管在每个单独的总体中观察到微小的变异性（图2A，B），但每个总体在PCA分析图上形成了一个不同的聚类（图2C）。
图3A显示了叠加在酿酒酵母YM427114芽酵母群的原始CRM图像上的精确3D细胞分割的结果。图3B显示了由此产生的群体的先天荧光特征。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61120/61120fig1v2.jpg"> 图1:分割的准确性和明显的种内变异性。（A）细菌细胞的典型单细胞先天荧光特征（P. putida KT2440），以光谱图（顶部）和热图（中间）表示。发射波长表示为彩虹色图（底部）。光谱图的Y轴和热图的颜色都表示相对荧光强度。底部的数字表示激发波长。通过图像分析算法识别准确（B）和不准确（C）细胞区域的可视化表示。浅蓝色阴影表示为土壤细菌 P. putida KT 2440 群体检测到的细胞区域。面板 C 中带有红色编号的 Blob 是错误检测的示例，其中算法由于不适当的二值化阈值设置而将非像元区域（即背景噪声）分类为像元区域。比例尺 = 1 μm。图D和E描绘了同一群体的先天荧光特征，分别通过准确和不准确的细胞分割生成。 每列显示重建的单细胞高光谱，呈现为1 x 192基质，其中黄色至蓝色的色图表示相对荧光强度。（F）使用PCA可视化的准确（浅蓝色）和不准确（红色）分割中先天荧光特征的方差。每个轴标签表示组件编号及其对 PCA 分析的累积百分比贡献。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61120/61120fig1v2large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61120/61120fig2v2.jpg"> 图2:先天荧光特征的种内和种间变异性。先天荧光特征以P. putida KT2440（A）和P. putida KT2442（B）种群的热图表示。（C）使用PCA可视化的两个先天荧光特征对的投影，对应于P. putida KT2440（红色，n = 288）和P. putida KT2442（蓝色，n = 373）。X 轴和 Y 轴分别代表 PC1 和 PC2。插图号表示每个簇的中心（1:P. putida KT2440，2:P. putida KT2442）。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61120/61120fig2v2large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61120/61120fig3v2.jpg"> 图3:3D分割和先天荧光特征提取的示例。 （A）对被识别为酿酒酵母萌芽酵母YM4271细胞群的区域进行3D投影。插页码是标识号。（B）从3D区域提取的先天荧光特征的热图。X 轴编号对应于标识号。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61120/61120fig3v2large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>

Watch this Scientific Journal Video about Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy at JoVE.com

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

在这里，提出了一种方案，用于光学提取和编目来自分布在三维空间中的每个个体活细胞的先天细胞荧光特征（即细胞自发荧光）。该方法适用于以单细胞分辨率研究各种生物系统的先天荧光特征，包括来自细菌，真菌，酵母，植物和动物的细胞。

通过共聚焦显微镜重建单细胞先天荧光特征

Described here is confocal reflection microscopy-assisted single-cell innate fluorescence analysis (CRIF), a minimally invasive method for reconstructing ...

reconstruction-single-cell-innate-fluorescence-signatures-confocal

Nanyang Technological University

Research

JoVE Journal

Biology

2.7K 次观看.  University of Tsukuba. 在这里，提出了一种方案，用于光学提取和编目来自分布在三维空间中的每个个体活细胞的先天细胞荧光特征（即细胞自发荧光）。该方法适用于以单细胞分辨率研究各种生物系统的先天荧光特征，包括来自细菌，真菌，酵母，植物和动物的细胞。

视频: Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

受体动力学通过单分子荧光显微镜的高分辨率时空分析

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

科研

生物工程

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to conventional epi-fluorescence microscopy, various imaging techniques have been developed to achieve specific experimental goals. Some of the widely used techniques include single-molecule fluorescence resonance energy transfer (smFRET), which can report conformational changes and molecular interactions with angstrom resolution, and single-molecule detection-based super-resolution (SR) imaging, which can enhance the spatial resolution approximately ten&#160;to twentyfold compared to diffraction-limited microscopy. Here we present a customer-designed integrated system, which merges multiple imaging methods in one microscope, including conventional epi-fluorescent imaging, single-molecule detection-based SR imaging, and multi-color single-molecule detection, including smFRET imaging. Different imaging methods can be achieved easily and reproducibly by switching optical elements. This set-up is easy to adopt by any research laboratory in biological sciences with a need for routine and diverse imaging experiments at a reduced cost and space relative to building separate microscopes for individual purposes.

Here we present a practical guide of building an integrated microscopy system, which merges conventional epi-fluorescent imaging, single-molecule detection-based super-resolution imaging, and multi-color single-molecule detection, including single-molecule fluorescence resonance energy transfer imaging, into one set-up in a cost-efficient way.

使用一个荧光显微镜进行多种成像模式

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to ...

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 ...

免疫与感染

Quantification of Efferocytosis by Single-cell Fluorescence Microscopy

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling and cellular processes that control efferocytosis. This quantification can be difficult to perform as apoptotic cells are often efferocytosed piecemeal, thus necessitating methods which can accurately delineate between the efferocytosed portion of an apoptotic target versus residual unengulfed cellular fragments. The approach outlined herein utilizes dual-labeling approaches to accurately quantify the dynamics of efferocytosis and efferocytic capacity of efferocytes such as macrophages. The cytosol of the apoptotic cell is labeled with a cell-tracking dye to enable monitoring of all apoptotic cell-derived materials, while surface biotinylation of the apoptotic cell allows for differentiation between internalized and non-internalized apoptotic cell fractions. The efferocytic capacity of efferocytes is determined by taking fluorescent images of live or fixed cells and quantifying the amount of bound versus internalized targets, as differentiated by streptavidin staining. This approach offers several advantages over methods such as flow cytometry, namely the accurate delineation of non-efferocytosed versus efferocytosed apoptotic cell fractions, the ability to measure efferocytic dynamics by live-cell microscopy, and the capacity to perform studies of cellular signaling in cells expressing fluorescently-labeled transgenes. Combined, the methods outlined in this protocol serve as the basis for a flexible experimental approach that can be used to accurately quantify efferocytic activity and interrogate cellular signaling pathways active during efferocytosis.

Efferocytosis, the phagocytic removal of apoptotic cells, is required to maintain homeostasis and is facilitated by receptors and signaling pathways that allow for the recognition, engulfment, and internalization of apoptotic cells. Herein, we present a fluorescence microscopy protocol for the quantification of efferocytosis and the activity of efferocytic signaling pathways.

单细胞荧光显微镜定量 Efferocytosis 的研究

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling ...

Three-dimensional Imaging of Bacterial Cells for Accurate Cellular Representations and Precise Protein Localization

The shape of a bacterium is important for its physiology. Many aspects of cell physiology such as cell motility, predation, and biofilm production can be affected by cell shape. Bacterial cells are three-dimensional (3D) objects, although they are rarely treated as such. Most microscopy techniques result in two-dimensional (2D) images leading to the loss of data pertaining to the actual 3D cell shape and localization of proteins. Certain shape parameters, such as Gaussian curvature (the product of the two principal curvatures), can only be measured in 3D because 2D images do not measure both principal curvatures. Additionally, not all cells lie flat when mounting and 2D imaging of curved cells may not accurately represent the shapes of these cells. Accurately measuring protein localization in 3D can help determine the spatial regulation and function of proteins. A forward convolution technique has been developed that uses the blurring function of the microscope to reconstruct 3D cell shapes and to accurately localize proteins. Here, a protocol for preparing and mounting samples for live cell imaging of bacteria in 3D both to reconstruct an accurate cell shape and to localize proteins is described. The method is based on simple sample preparation, fluorescent image acquisition, and MATLAB-based image processing. Many high-quality fluorescent microscopes can be simply modified to take these measurements. These cell reconstructions are computationally intensive and access to high-throughput computational resources is recommended, although not necessary. This method has been successfully applied to multiple bacterial species and mutants, fluorescent imaging modalities, and microscope manufacturers.

This protocol explains how to prepare and mount bacterial samples for live three-dimensional imaging and how to reconstruct the three-dimensional shape of E. coli from those images.

细菌细胞的三维成像，实现精确的细胞表现和精确的蛋白质定位

The shape of a bacterium is important for its physiology. Many aspects of cell physiology such as cell motility, predation, and biofilm production can be ...

Super-resolution Imaging of the Bacterial Division Machinery

Bacterial cell division requires the coordinated assembly of more than ten essential proteins at midcell1,2. Central to this process is the formation of a ring-like suprastructure (Z-ring) by the FtsZ protein at the division plan3,4. The Z-ring consists of multiple single-stranded FtsZ protofilaments, and understanding the arrangement of the protofilaments inside the Z-ring will provide insight into the mechanism of Z-ring assembly and its function as a force generator5,6. This information has remained elusive due to current limitations in conventional fluorescence microscopy and electron microscopy. Conventional fluorescence microscopy is unable to provide a high-resolution image of the Z-ring due to the diffraction limit of light (~200 nm). Electron cryotomographic imaging has detected scattered FtsZ protofilaments in small C. crescentus cells7, but is difficult to apply to larger cells such as E. coli or B. subtilis. Here we describe the application of a super-resolution fluorescence microscopy method, Photoactivated Localization Microscopy (PALM), to quantitatively characterize the structural organization of the E. coli Z-ring8.
	PALM imaging offers both high spatial resolution (~35 nm) and specific labeling to enable unambiguous identification of target proteins. We labeled FtsZ with the photoactivatable fluorescent protein mEos2, which switches from green fluorescence (excitation = 488 nm) to red fluorescence (excitation = 561 nm) upon activation at 405 nm9. During a PALM experiment, single FtsZ-mEos2 molecules are stochastically activated and the corresponding centroid positions of the single molecules are determined with &lt;20 nm precision. A super-resolution image of the Z-ring is then reconstructed by superimposing the centroid positions of all detected FtsZ-mEos2 molecules.
	Using this method, we found that the Z-ring has a fixed width of ~100 nm and is composed of a loose bundle of FtsZ protofilaments that overlap with each other in three dimensions. These data provide a springboard for further investigations of the cell cycle dependent changes of the Z-ring10 and can be applied to other proteins of interest.

We describe a super-resolution imaging method to probe the structural organization of the bacterial FtsZ-ring, an essential apparatus for cell division. This method is based on quantitative analyses of photoactivated localization microscopy (PALM) images and can be applied to other bacterial cytoskeletal proteins.

超分辨率成像细菌科机械

Bacterial cell division requires the coordinated  assembly of more than ten essential proteins at midcell1,2. Central  to this process is the formation of ...

生物学

In vivo Clonal Tracking of Hematopoietic Stem and Progenitor Cells Marked by Five Fluorescent Proteins using Confocal and Multiphoton Microscopy

We developed and validated a fluorescent marking methodology for clonal tracking of hematopoietic stem and progenitor cells (HSPCs) with high spatial and temporal resolution to study in vivo hematopoiesis using the murine bone marrow transplant experimental model. Genetic combinatorial marking using lentiviral vectors encoding fluorescent proteins (FPs) enabled cell fate mapping through advanced microscopy imaging. Vectors encoding five different FPs: Cerulean, EGFP, Venus, tdTomato, and mCherry were used to concurrently transduce HSPCs, creating a diverse palette of color marked cells. Imaging using confocal/two-photon hybrid microscopy enables simultaneous high resolution assessment of uniquely marked cells and their progeny in conjunction with structural components of the tissues. Volumetric analyses over large areas reveal that spectrally coded HSPC-derived cells can be detected non-invasively in various intact tissues, including the bone marrow (BM), for extensive periods of time following transplantation. Live studies combining video-rate multiphoton and confocal time-lapse imaging in 4D demonstrate the possibility of dynamic cellular and clonal tracking in a quantitative manner.

In vivo Clonal Tracking of Hematopoietic Stem and Progenitor Cells Marked by Five Fluorescent Proteins using Confocal and Multiphoton Microscopy

Combinatorial 5 fluorescent proteins marking of hematopoietic stem and progenitor cells allows in vivo clonal tracking via confocal and two-photon microscopy, providing insights into bone marrow hematopoietic architecture during regeneration. This method allows non-invasive fate mapping of spectrally-coded HSPCs-derived cells in intact tissues for extensive periods of time following transplantation.

在造血干细胞和祖细胞利用共聚焦和多光子显微镜五荧光蛋白标记的活体克隆跟踪

We developed and validated a fluorescent marking methodology for clonal tracking of hematopoietic stem and progenitor cells (HSPCs) with high spatial and ...

Internalization and Observation of Fluorescent Biomolecules in Living Microorganisms via Electroporation

The ability to study biomolecules in vivo is crucial for understanding their function in a biological context. One powerful approach involves fusing molecules of interest to fluorescent proteins such as GFP to study their expression, localization and function. However, GFP and its derivatives are significantly larger and less photostable than organic fluorophores generally used for in vitro experiments, and this can limit the scope of investigation. 
We recently introduced a straightforward, versatile and high-throughput method based on electroporation, allowing the internalization of biomolecules labeled with organic fluorophores into living microorganisms. Here we describe how to use electroporation to internalize labeled DNA fragments or proteins into Escherichia coli and Saccharomyces cerevisi&#230;, how to quantify the number of internalized molecules using fluorescence microscopy, and how to quantify the viability of electroporated cells. Data can be acquired at the single-cell or single-molecule level using fluorescence or FRET. The possibility of internalizing non-labeled molecules that trigger a physiological observable response in vivo is also presented. Finally, strategies of optimization of the protocol for specific biological systems are discussed.

Studies of biomolecules in vivo are crucial for understanding molecular function in a biological context. Here we describe a novel method allowing the internalization of fluorescent biomolecules, such as DNA or proteins, into living microorganisms. Analysis of in vivo data recorded by fluorescence microscopy is also presented and discussed.

通过电穿孔内在和生物分子荧光观察生活中的微生物

The ability to study biomolecules in vivo is crucial for understanding their function in a biological context. One powerful approach involves fusing ...

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

Confocal microscopy provides an accessible methodology to capture sub-cellular interactions critical for the characterization and further development of pre-clinical agents labeled with fluorescent probes. With recent advancements in antibody based cytotoxic drug delivery systems, understanding the alterations induced by these agents within the realm of receptor aggregation and internalization is of critical importance. This protocol leverages the well-established methodology of fluorescent immunocytochemistry and the open source FIJI distribution of ImageJ, with its inbuilt autocorrelation and image mathematical functions, to perform spatial image correlation spectroscopy (ICS). This protocol quantitates the fluorescent intensity of labeled receptors as a function of the beam area of the confocal microscope. This provides a quantitative measure of the state of target molecule aggregation on the cell surface. This methodology is focused on the characterization of static cells with potential to expand into temporal investigations of receptor aggregation. This protocol presents an accessible methodology to provide quantification of clustering events occurring at the cell surface, utilizing well established techniques and non-specialized imaging apparatus.

Antibodies that bind to target receptors on the cell surface can confer conformation and clustering alterations. These dynamic changes have implications for characterizing drug development in target cells. This protocol utilizes confocal microscopy and image correlation spectroscopy through ImageJ/FIJI to quantify the extent of receptor clustering on the cell surface.

共聚焦显微镜通过图像相关谱揭示细胞表面受体聚集

Confocal microscopy provides an accessible methodology to capture sub-cellular interactions critical for the characterization and further development of ...

可定制的荧光显微镜，用于可视化细胞骨架网络

Design and Building of a Customizable, Single-Objective, Light-Sheet Fluorescence Microscope for the Visualization of Cytoskeleton Networks

Reconstituted cytoskeleton composites have emerged as a valuable model system for studying non-equilibrium soft matter. The faithful capture of the dynamics of these 3D, dense networks calls for optical sectioning, which is often associated with fluorescence confocal microscopes. However, recent developments in light-sheet fluorescence microscopy (LSFM) have established it as a cost-effective and, at times, superior alternative. To make LSFM accessible to cytoskeleton researchers less familiar with optics, we present a step-by-step beginner's guide to building a versatile light-sheet fluorescence microscope from off-the-shelf components. To enable sample mounting with traditional slide samples, this LSFM follows the single-objective light-sheet (SOLS) design, which utilizes a single objective for both the excitation and emission collection. We describe the function of each component of the SOLS in sufficient detail to allow readers to modify the instrumentation and design it to fit their specific needs. Finally, we demonstrate the use of this custom SOLS instrument by visualizing asters in kinesin-driven microtubule networks.

作者聚焦:通过光片显微镜推进远非平衡材料知识

This protocol describes in detail how to build a single-objective, light-sheet fluorescence microscope and its usage for visualizing cytoskeleton networks.

设计和构建用于细胞骨架网络可视化的可定制、单物镜、光片荧光显微镜

Reconstituted cytoskeleton composites have emerged as a valuable model system for studying non-equilibrium soft matter. The faithful capture of the ...