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 border="0" cellpadding="0" cellspacing="0" style="width:720px;" width="720">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Agarose</td>
			<td style="width:220px;">Wako Chemicals</td>
			<td style="width:119px;">312-01193</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="105">
			<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。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

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 ...

Cell Electrofusion Visualized with Fluorescence Microscopy

Cell electrofusion is a safe, non-viral and non-chemical method that can be used for preparing hybrid cells for human therapy. Electrofusion involves application of short high-voltage electric pulses to cells that are in close contact. Application of short, high-voltage electric pulses causes destabilization of cell plasma membranes. Destabilized membranes are more permeable for different molecules and also prone to fusion with any neighboring destabilized membranes. Electrofusion is thus a convenient method to achieve a non-specific fusion of very different cells in vitro. In order to obtain fusion, cell membranes, destabilized by electric field, must be in a close contact to allow merging of their lipid bilayers and consequently their cytoplasm. In this video, we demonstrate efficient electrofusion of cells in vitro by means of modified adherence method. In this method, cells are allowed to attach only slightly to the surface of the well, so that medium can be exchanged and cells still preserve their spherical shape. Fusion visualization is assessed by pre-labeling of the cytoplasm of cells with different fluorescent cell tracker dyes; half of the cells are labeled with orange CMRA and the other half with green CMFDA. Fusion yield is determined as the number of dually fluorescent cells divided with the number of all cells multiplied by two.

In this video we demonstrate efficient electrofusion of cells in vitro by means of modified adherence method using electroporation and the subsequent detection of fused cells visualization with fluorescence microscopy.

荧光显微镜下细胞电融合的可视化

Cell electrofusion is a safe, non-viral and non-chemical method that can be used for preparing hybrid cells for human therapy. Electrofusion involves ...

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 ...

Analyzing Craniofacial Morphogenesis in Zebrafish Using 4D Confocal Microscopy

Time-lapse imaging is a technique that allows for the direct observation of the process of morphogenesis, or the generation of shape. Due to their optical clarity and amenability to genetic manipulation, the zebrafish embryo has become a popular model organism with which to perform time-lapse analysis of morphogenesis in living embryos. Confocal imaging of a live zebrafish embryo requires that a tissue of interest is persistently labeled with a fluorescent marker, such as a transgene or injected dye. The process demands that the embryo is anesthetized and held in place in such a way that healthy development proceeds normally. Parameters for imaging must be set to account for three-dimensional growth and to balance the demands of resolving individual cells while getting quick snapshots of development. Our results demonstrate the ability to perform long-term in vivo imaging of fluorescence-labeled zebrafish embryos and to detect varied tissue behaviors in the cranial neural crest that cause craniofacial abnormalities. Developmental delays caused by anesthesia and mounting are minimal, and embryos are unharmed by the process. Time-lapse imaged embryos can be returned to liquid medium and subsequently imaged or fixed at later points in development. With an increasing abundance of transgenic zebrafish lines and well-characterized fate mapping and transplantation techniques, imaging any desired tissue is possible. As such, time-lapse in vivo imaging combines powerfully with zebrafish genetic methods, including analyses of mutant and microinjected embryos.

Time-lapse confocal imaging is a powerful technique useful for characterizing embryonic development. Here, we describe the methodology and characterize craniofacial morphogenesis in wild-type, as well as pdgfra, smad5, and smo mutant embryos.

使用4D共聚焦显微镜分析颅面形态的斑马鱼

Time-lapse imaging is a technique that allows for the direct observation of the process of morphogenesis, or the generation of shape. Due to their optical ...

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 ...

Isolation and Fluorescence Imaging for Single-particle Reconstruction of Chlamydomonas Centrioles

Centrioles are large macromolecular assemblies important for the proper execution of fundamental cell biological processes such as cell division, cell motility, or cell signaling. The green algae Chlamydomonas reinhardtii has proven to be an insightful model in the study of centriole architecture, function, and protein composition. Despite great advances toward understanding centriolar architecture, one of the current challenges is to determine the precise localization of centriolar components within structural regions of the centriole in order to better understand their role in centriole biogenesis. A major limitation lies in the resolution of fluorescence microscopy, which complicates the interpretation of protein localization in this organelle with dimensions close to the diffraction limit. To tackle this question, we are providing a method to purify and image a large number of C. reinhardtii centrioles with different orientations using super-resolution microscopy. This technique allows further processing of data through fluorescent single-particle averaging (Fluo-SPA) owing to the large number of centrioles acquired. Fluo-SPA generates averages of stained C. reinhardtii centrioles in different orientations, thus facilitating the localization of distinct proteins in centriolar sub-regions. Importantly, this method can be applied to image centrioles from other species or other large macromolecular assemblies.

Isolation and Fluorescence Imaging for Single-particle Reconstruction of Chlamydomonas Centrioles

We have developed a strategy to purify and image a large number of centrioles in different orientations amenable for super-resolution microscopy and single-particle averaging.

衣藻中心粒单粒子重建的分离与荧光成像

Centrioles are large macromolecular assemblies important for the proper execution of fundamental cell biological processes such as cell division, cell ...

Direct Stochastic Optical Reconstruction Microscopy of Extracellular Vesicles in Three Dimensions

Extracellular vesicles (EVs) are released by all cell types and play an important role in cell signaling and homeostasis. The visualization of EVs often require indirect methods due to their small diameter (40-250 nm), which is beneath the diffraction limit of typical light microscopy. We have developed a super-resolution microscopy-based visualization of EVs to bypass the diffraction limit in both two and three dimensions. Using this approach, we can resolve the three-dimensional shape of EVs to within +/- 20 nm resolution on the XY-axis and +/- 50 nm resolution along the Z-axis. In conclusion, we propose that super-resolution microscopy be considered as a characterization method of EVs, including exosomes, as well as enveloped viruses.

Direct stochastic optical reconstruction microscopy (dSTORM) is used to bypass the typical diffraction limit of light microscopy and to view exosomes at the nanometer scale. It can be employed in both two and three dimensions to characterize exosomes.

三维细胞外囊泡的直接随机光学重建显微镜

Extracellular vesicles (EVs) are released by all cell types and play an important role in cell signaling and homeostasis. The visualization of EVs often ...