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?...

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。

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			<td height="21" style="height:21px;width:215px;">Agarose</td>
			<td style="width:220px;">Wako Chemicals</td>
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			<td height="105" style="height:105px;width:215px;">Beam splitters</td>
			<td style="width:220px;">Carl Zeiss, Nikon</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">MBSInVis405, MBS458, MBS488, MBS458/514, MBS488/543, or MBS 488/543/633 beam splitters (Carl Zeiss)</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:215px;">Confocal microscope</td>
			<td style="width:220px;">Carl Zeiss, Nikon</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Model LSM 880 (Carl Zeiss), Model A1R (Nikon)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Cover slips</td>
			<td style="width:220px;">Matsunami Glass</td>
			<td style="width:119px;">C024601</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Glass slides</td>
			<td style="width:220px;">Matsunami Glass</td>
			<td style="width:119px;">S011120</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Half-reflection mirror</td>
			<td style="width:220px;">Carl Zeiss, Nikon</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">NT80/20</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:215px;">Laser power meter</td>
			<td style="width:220px;">Thorlabs</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">PM400 (power meter console) and S175C (sensor)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">LB Broth</td>
			<td style="width:220px;">Nacalai tesque</td>
			<td style="width:119px;">20066-95</td>
			<td>For bacteria culture</td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:215px;">Image analysis software</td>
			<td style="width:220px;">The MathWorks</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">MATLAB version 2019a or later, Image Processing Toolbox is needed</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:215px;">Microscope objective</td>
			<td style="width:220px;">Carl Zeiss, Nikon</td>
			<td style="width:119px;">440762-9904</td>
			<td style="width:167px;">e.g. 63x plan Apochomat NA = 1.4 (Carl Zeiss)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:215px;">Microscope software</td>
			<td style="width:220px;">Carl Zeiss, Nikon</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">ZEN (Carl Zeiss),NIS-elements (Nikon)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">PBS(-)</td>
			<td style="width:220px;">Wako Chemicals</td>
			<td style="width:119px;">166-23555</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="147">
			<td height="147" style="height:147px;width:215px;">Programming language</td>
			<td style="width:220px;"></td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Python and libraries, modules (numpy, scikit-learn, scikit-image, os, glob, matplotlib, tkinter) are rquired to run the supplied PCA script.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Silicone gasket</td>
			<td style="width:220px;">ThermoFisher Scientific</td>
			<td style="width:119px;">P24744</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:215px;">Workstation</td>
			<td style="width:220px;"></td>
			<td style="width:119px;"></td>
			<td style="width:167px;">A high-performance workstation with discrete GPUs is recommended.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:215px;">Yeast extract-peptone-dextrose (YPD) agar medium</td>
			<td style="width:220px;">Sigma-Aldrich</td>
			<td style="width:119px;">Y1500-250G</td>
			<td>For yeast culture</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">YPD medium</td>
			<td style="width:220px;">Sigma-Aldrich</td>
			<td style="width:119px;">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...

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

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

Live Imaging of the Zebrafish Embryonic Brain by Confocal Microscopy

In this video, we demonstrate the method our lab has developed to analyze the cell shape changes and rearrangements required to bend and fold the developing zebrafish brain (Gutzman et al, 2008). Such analysis affords a new understanding of the underlying cell biology required for development of the 3D structure of the vertebrate brain, and significantly increases our ability to study neural tube morphogenesis. The embryonic zebrafish brain is shaped beginning at 18 hours post fertilization (hpf) as the ventricles within the neuroepithelium inflate. By 24 hpf, the initial steps of neural tube morphogenesis are complete. Using the method described here, embryos at the one cell stage are injected with mRNA encoding membrane-targeted green fluorescent protein (memGFP). After injection and incubation, the embryo, now between 18 and 24 hpf, is mounted, inverted, in agarose and imaged by confocal microscopy. Notably, the zebrafish embryo is transparent making it an ideal system for fluorescent imaging. While our analyses have focused on the midbrain-hindbrain boundary and the hindbrain, this method could be extended for analysis of any region in the zebrafish to a depth of 
80-100 &mu;m.

In this video, we demonstrate a method by which to analyze the developing vertebrate brain in live zebrafish embryos at single cell resolution by confocal microscopy. This includes the method by which we inject the single-cell zebrafish embryo and subsequently mount and image the developing brain.

现场共聚焦显微镜对斑马鱼的胚胎脑成像

In this video, we demonstrate the method our lab has developed to analyze the cell shape changes and rearrangements required to bend and fold the ...

科研

生物学

Time-lapse Imaging of Mitosis After siRNA Transfection

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and cellular content. Hallmark events of mitosis, such as chromosome movement, can be readily tracked on an individual cell basis using time-lapse fluorescence microscopy of mammalian cell lines expressing specific GFP-tagged proteins. In combination with RNAi-based depletion, this can be a powerful method for pinpointing the stage(s) of mitosis where defects occur after levels of a particular protein have been lowered. In this protocol, we present a basic method for assessing the effect of depleting a potential mitotic regulatory protein on the timing of mitosis. Cells are transfected with siRNA, placed in a stage-top incubation chamber, and imaged using an automated fluorescence microscope. We describe how to use software to set up a time-lapse experiment, how to process the image sequences to make either still-image montages or movies, and how to quantify and analyze the timing of mitotic stages using a cell-line expressing mCherry-tagged histone H2B. Finally, we discuss important considerations for designing a time-lapse experiment. This strategy is complementary to other approaches and offers the advantages of 1) sensitivity to changes in kinetics that might not be observed when looking at cells as a population and 2) analysis of mitosis without the need to synchronize the cell cycle using drug treatments. The visual information from such imaging experiments not only allows the sub-stages of mitosis to be assessed, but can also provide unexpected insight that would not be apparent from cell cycle analysis by FACS.

Here we describe a basic protocol to image and quantify the mitotic timing of live mammalian tissue culture cells after siRNA transfection.

有丝分裂的siRNA转染后的时间推移成像

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and ...

Fluorescence-based Measurement of Store-operated Calcium Entry in Live Cells: from Cultured Cancer Cell to Skeletal Muscle Fiber

Store operated Ca2+ entry (SOCE), earlier termed capacitative Ca2+ entry, is a tightly regulated mechanism for influx of extracellular Ca2+ into cells to replenish depleted endoplasmic reticulum (ER) or sarcoplasmic reticulum (SR) Ca2+ stores1,2. Since Ca2+ is a ubiquitous second messenger, it is not surprising to see that SOCE plays important roles in a variety of cellular processes, including proliferation, apoptosis, gene transcription and motility. Due to its wide occurrence in nearly all cell types, including epithelial cells and skeletal muscles, this pathway has received great interest3,4. However, the heterogeneity of SOCE characteristics in different cell types and the physiological function are still not clear5-7.
The functional channel properties of SOCE can be revealed by patch-clamp studies, whereas a large body of knowledge about this pathway has been gained by fluorescence-based intracellular Ca2+ measurements because of its convenience and feasibility for high-throughput screening. The objective of this report is to summarize a few fluorescence-based methods to measure the activation of SOCE in monolayer cells, suspended cells and muscle fibers5,8-10. The most commonly used of these fluorescence methods is to directly monitor the dynamics of intracellular Ca2+ using the ratio of F340nm and F380nm (510 nm for emission wavelength) of the ratiometric Ca2+ indicator Fura-2. To isolate the activity of unidirectional SOCE from intracellular Ca2+ release and Ca2+ extrusion, a Mn2+ quenching assay is frequently used. Mn2+ is known to be able to permeate into cells via SOCE while it is impervious to the surface membrane extrusion processes or to ER uptake by Ca2+ pumps due to its very high affinity with Fura-2. As a result, the quenching of Fura-2 fluorescence induced by the entry of extracellular Mn2+ into the cells represents a measurement of activity of SOCE9. Ratiometric measurement and the Mn+2 quenching assays can be performed on a cuvette-based spectrofluorometer in a cell population mode or in a microscope-based system to visualize single cells. The advantage of single cell measurements is that individual cells subjected to gene manipulations can be selected using GFP or RFP reporters, allowing studies in genetically modified or mutated cells. The spatiotemporal characteristics of SOCE in structurally specialized skeletal muscle can be achieved in skinned muscle fibers by simultaneously monitoring the fluorescence of two low affinity Ca2+ indicators targeted to specific compartments of the muscle fiber, such as Fluo-5N in the SR and Rhod-5N in the transverse tubules9,11,12.

The extent of store-operated Ca2+ entry (SOCE) can be monitored using fluorescent Ca2+ indicators. Mn2+ quenching of such indicators assays SOCE in cultured cells and skeletal muscle fibers. A technique allowing spatial and temporal resolution of SOCE by confocal imaging of mechanically skinned muscle fibers is also described.

基于荧光测定活细胞中的钙进入商店经营：从培养的肿瘤细胞，骨骼肌纤维

Store operated Ca2+ entry (SOCE), earlier termed capacitative Ca2+ entry, is a tightly regulated mechanism for influx of extracellular Ca2+ into cells to ...

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 ...

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) maintain the turnover of all mature blood cell lineages. The coordination of the complex signals leading to specific HSC fates relies upon the interaction between HSCs and the intricate bone marrow microenvironment, which is still poorly understood[1-2].
We describe how by combining a newly developed specimen holder for stable animal positioning with multi-step confocal and two-photon in vivo imaging techniques, it is possible to obtain high-resolution 3D stacks containing HSPCs and their surrounding niches and to monitor them over time through multi-point time-lapse imaging. High definition imaging allows detecting ex vivo labeled hematopoietic stem and progenitor cells (HSPCs) residing within the bone marrow. Moreover, multi-point time-lapse 3D imaging, obtained with faster acquisition settings, provides accurate information about HSPC movement and the reciprocal interactions between HSPCs and stroma cells.
Tracking of HSPCs in relation to GFP positive osteoblastic cells is shown as an exemplary application of this method. This technique can be utilized to track any appropriately labeled hematopoietic or stromal cell of interest within the mouse calvarium bone marrow space.

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

The nature of the interactions between hematopoietic stem and progenitor cells (HSPCs) and bone marrow niches is poorly understood. Custom hardware modifications and a multi-step acquisition protocol allow the use of two-photon and confocal microscopy to image ex vivo labeled HSPCs homed within bone marrow areas, tracking interactions and movement.

在造血干细胞和祖细胞的成年小鼠颅骨骨髓体内四维跟踪

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) ...

Detection of Ligand-activated G Protein-coupled Receptor Internalization by Confocal Microscopy

Confocal laser scanning microscopy (CLSM) is an optical imaging technique for high-contrast imaging. It is a powerful approach to visualize fluorescent fusion proteins, such as green fluorescent protein (GFP), to determine their expression, localization, and function. The subcellular localization of target proteins is important for identification, characterization, and functional analyses. Internalization is one of the predominant mechanisms controlling G protein-coupled receptor (GPCR) signaling to ensure the appropriate cellular responses to stimuli. Here, we describe an experimental method to detect the subcellular localization and internalization of GPCR in HEK293 cells with confocal microscopy. In addition, this experiment provides some details about cell culture and transfection. This protocol is compatible with a variety of widely available fluorescent markers and is applicable to the visualization of the subcellular localization of a majority of proteins, as well as of the internalization of GPCR. This technique should enable researchers to efficiently manipulate GPCR gene expression in mammalian cell lines and should facilitate studies on GPCR subcellular localization and internalization.

This protocol describes confocal microscopy detection of G protein-coupled receptor (GPCR) internalization in mammalian cells. It includes the basic cell culture, transfection, and confocal microscopy procedure and provides an efficient and easily interpretable method to detect the subcellular localization and internalization of fusion-expressed GPCR.

配体激活的G蛋白偶联受体内在化的检测通过共聚焦显微镜

Confocal laser scanning microscopy (CLSM) is an optical imaging technique for high-contrast imaging. It is a powerful approach to visualize fluorescent ...

Quantification of Interbacterial Competition using Single-Cell Fluorescence Imaging

Interbacterial competition can directly impact the structure and function of microbiomes. This work describes a fluorescence microscopy approach that can be used to visualize and quantify competitive interactions between different bacterial strains at the single-cell level. The protocol described here provides methods for advanced approaches in slide preparation on both upright and inverted epifluorescence microscopes, live-cell and time-lapse imaging techniques, and quantitative image analysis using the open-source software FIJI. The approach in this manuscript outlines the quantification of competitive interactions between symbiotic Vibrio fischeri populations by measuring the change in area over time for two coincubated strains that are expressing different fluorescent proteins from stable plasmids. Alternative methods are described for optimizing this protocol in bacterial model systems that require different growth conditions. Although the assay described here uses conditions optimized for V. fischeri, this approach is highly reproducible and can easily be adapted to study competition among culturable isolates from diverse microbiomes.

This manuscript describes a method for using single-cell fluorescence microscopy to visualize and quantify bacterial competition in coculture.

使用单细胞荧光成像对菌际竞争进行量化

Interbacterial competition can directly impact the structure and function of microbiomes. This work describes a fluorescence microscopy approach that can ...

Autofluorescence Imaging to Evaluate Red Algae Physiology

Red algae (Rhodophyta) contain phycobiliproteins and colonize habitats with dim light, however some (e.g., some Chroothece species) can also develop in full sunshine. Most rhodophytes are red, however some can appear bluish, depending on the proportion of blue and red biliproteins (phycocyanin and phycoerythrin). Different phycobiliproteins can capture light at diverse wavelengths and transmit it to chlorophyll a, which makes photosynthesis under very different light conditions possible. These pigments respond to habitat changes in light, and their autofluorescence can help to study biological processes. Using Chroothece mobilis as a model organism and the spectral lambda scan mode in a confocal microscope, the adaptation of photosynthetic pigments to different monochromatic lights was studied at the cellular level to guess the species' optimal growth conditions. The results showed that, even when the studied strain was isolated from a cave, it adapted to both dim and medium light intensities. The presented method is especially useful for studying photosynthetic organisms that do not grow or grow very slowly under laboratory conditions, which is usually the case for those living in extreme habitats.

The present protocol describes step-by-step autofluorescence imaging and evaluation of phycobiliprotein changes in red algae based on spectral analysis. This is a label-free and non-destructive method to evaluate cellular adaptation to extreme habitats, when only scarce material is available and cells grow slowly, or not at all, under laboratory conditions.

自发荧光成像评估红藻生理学

Red algae (Rhodophyta) contain phycobiliproteins and colonize habitats with dim light, however some (e.g., some Chroothece species) can also develop in ...

Isolation and Transcriptome Analysis of Plant Cell Types

In multicellular organisms, developmental programming and environmental responses can be highly divergent in different cell types or even within cells, which is known as cellular heterogeneity. In recent years, single-cell and cell-type isolation combined with next-generation sequencing (NGS) techniques have become important tools for studying biological processes at single-cell resolution. However, isolating plant cells is relatively more difficult due to the presence of plant cell walls, which limits the application of single-cell approaches in plants. This protocol describes a robust procedure for fluorescence-activated cell sorting (FACS)-based single-cell and cell-type isolation with plant cells, which is suitable for downstream multi-omics analysis and other studies. Using Arabidopsis root fluorescent marker lines, we demonstrate how particular cell types, such as xylem-pole pericycle cells, lateral root initial cells, lateral root cap cells, cortex cells, and endodermal cells, are isolated. Furthermore, an effective downstream transcriptome analysis method using Smart-seq2 is also provided. The cell isolation method and transcriptome analysis techniques can be adapted to other cell types and plant species and have broad application potential in plant science.

The feasibility and effectiveness of high-throughput scRNA-seq methods herald a single-cell era in plant research. Presented here is a robust and complete procedure for isolating specific Arabidopsis thaliana root cell types and subsequent transcriptome library construction and analysis.

植物细胞类型的分离和转录组分析

In multicellular organisms, developmental programming and environmental responses can be highly divergent in different cell types or even within cells, ...

使用 mtHyper7 对活酵母细胞中的线粒体过氧化物进行成像

Imaging of mtHyPer7, a Ratiometric Biosensor for Mitochondrial Peroxide, in Living Yeast Cells

Mitochondrial dysfunction, or functional alteration, is found in many diseases and conditions, including neurodegenerative and musculoskeletal disorders, cancer, and normal aging. Here, an approach is described to assess mitochondrial function in living yeast cells at cellular and subcellular resolutions using a genetically encoded, minimally invasive, ratiometric biosensor. The biosensor, mitochondria-targeted HyPer7 (mtHyPer7), detects hydrogen peroxide (H2O2) in mitochondria. It consists of a mitochondrial signal sequence fused to a circularly permuted fluorescent protein and the H2O2-responsive domain of a bacterial OxyR protein. The biosensor is generated and integrated into the yeast genome using a CRISPR-Cas9 marker-free system, for&#160;more consistent expression compared to plasmid-borne constructs.
mtHyPer7 is quantitatively targeted to mitochondria, has no detectable effect on yeast growth rate or mitochondrial morphology, and provides a quantitative readout for mitochondrial H2O2 under normal growth conditions and upon exposure to oxidative stress. This protocol explains how to optimize imaging conditions using a spinning-disk confocal microscope system and perform quantitative analysis using freely available software. These tools make it possible to collect rich spatiotemporal information on mitochondria both within cells and among cells in a population. Moreover, the workflow described here can be used to validate other biosensors.

作者聚焦：推进线粒体研究 - 用于亚细胞分析的 mtHyper7 生物传感器 

Hydrogen peroxide (H2O2) is both a source of oxidative damage and a signaling molecule. This protocol describes how to measure mitochondrial H2O2 using mitochondria-targeted HyPer7 (mtHyPer7), a genetically encoded ratiometric biosensor, in living yeast. It details how to optimize imaging conditions and perform quantitative cellular and subcellular analysis using freely available software.

mtHyPer7（一种用于线粒体过氧化物的比例生物传感器）在活酵母细胞中的成像

Mitochondrial dysfunction, or functional alteration, is found in many diseases and conditions, including neurodegenerative and musculoskeletal disorders, ...