作者没有什么可承认的。

1. 细胞培养监测采集
<ol><li>在 DMEM + 谷氨酰胺 (例如, GlutaMAX) 中生长 HeLa 细胞, 辅以 10% (v/v) 热灭活胎小牛血清和1% 青霉素和链霉素。</li>
	<li>涂层6井玻璃底部培养板与纤维连接蛋白 (25 µg/毫升) 为 1 h。然后每个井种子 2 x 104单元格。</li>
	<li>在购置期间, 每3天更换一次培养基。</li>
	<li>对于延时采集, 使用视频无透镜显微镜 (商用)。 注: 这是基于无透镜的计算成像技术, 如欧兹坎et . 所述。16 , 它被修改为在孵化器中以37摄氏度12、15的控制温度执行连续监视。它具有一个互补的金属氧化物半导体 (CMOS) 图像传感器, 像素间距为1.67 µm, 成像面积为 6.4 x 4.6 毫米2。多波长照明由一个多芯片组件发光二极管 (led) 装置提供, 它提供红色、绿色和蓝色照明。波长分别为636、521和 452 nm, 其光谱带宽分别为25、45和 25 nm。红绿蓝 (RGB) 发光二极管位于150µm 针孔的上方, 距离细胞约5厘米。测量接近 LED 的光功率低至10µW 在每个波长和照明时间仅一秒每承购。因此, 在无透镜的视镜下观察细胞培养时, 不会出现光毒性问题。</li>
	<li>将单元格区域性容器与 CMOS 传感器 (图 1) 联系在一起。在底部使用带有玻璃盖玻片的容器, 这对无透镜采集的质量很重要。还可以使用塑料容器, 但由于这些容器的光学质量较差, 无透镜采集将被降级。</li>
	<li>使用采集软件 (商用) 控制视频无透镜显微镜, 既可实现定时采集, 又可进行全息重建。用户在软件界面中需要输入的参数包括帧速率、实验持续时间和细胞培养类型, 即黏附细胞或漂浮细胞。</li>
	<li>设置采集软件的输入参数。每10分钟将帧速率设置为一次获取, 并将单元格区域性类型设置为 "粘附"。 注意: 每10分钟一次获取帧速率是一个很好的折衷, 因为它确保了可靠的单元跟踪, 而结果数据集的大小仍然是合理的。最快的帧速率可实现与这种无透镜显微镜设置是每5分钟一次获得。进一步增加帧率导致 CMOS 传感器过度加热, 这会影响细胞在培养中的生存能力。</li>
	<li>启动延时采集, 全息重建算法 (商用) 将自动处理无透镜采集, 获得细胞培养的相位图像。全息重建算法是基于多波长相位检索算法17 , 并提供一个 RGB 重建相图像的范围内的每一个单一的单元格 (π, + π) 在一个大视野的29.4 毫米2。无透镜在线全息术的原理是在 z=0 上用平面波 (在正常化后的振幅 1) 来照亮一个稀薄的样本, 并在 CMOS 传感器上检测随后的衍射强度图像在短距离 z = z, 通常为1毫米后,示例.在我们的设置中, 光照按顺序切换到3波长 (λ1= 0.450 µm, λ2= 0.540 µm, λ3= 0.647 µm) 来测量同一样本的三衍射模式。</li>
</ol>2. 细胞培养数据分析
<ol><li>对于单元跟踪, 使用 Trackmate 算法, 一个开源斐济插件, 用于自动跟踪单个粒子18。首先, 将全部的时间推移捕获加载到斐济 (加载图像序列命令)。由于数据集的大小很大, 通常 400 RGB 帧为 29.7 Mb, 因此以8位格式加载它们会更快。接下来, Trackmate 斐济插件引导用户通过细胞跟踪算法的几个阶段, 即单元检测阶段、单元跟踪阶段以及用于单元检测和计算轨道的几个滤镜。在每个阶段, 配置算法并立即显示结果, 以便在必要时可以轻松地来回导航以重新调整设置。Trackmate 接口的各种菜单显示在图 2中, 其中的实际设置用于 HeLa 单元实验。</li>
	<li>将采集软件的输入参数设置为如下 (请参见图 2)。将估计的 blob 直径设置为15像素, 探测器阈值为 0.25, 链接最大距离为15像素, 间隙闭合最大距离为15像素, 轨道中的点数为3.5。 注意: 这些设置明显不同于一个实验, 特别是与单元格大小对应的 "估计 blob 直径" (这里给出的像素为1.67 µm)。同样的评论也适用于 "链接最大距离", 它解释了在两个连续帧 (这里给出的像素为1.67 µm) 的最大距离。它的最佳值取决于细胞的运动, 也依赖于细胞密度。</li>
	<li>在单元格跟踪过程的末尾, 以三个文本文件 ("分析" 按钮) 的形式生成结果, 请参见图 2)。最有用的文件, 名为 "轨道统计" 中的 "点", 由一个表列出所有检测到的单元格, 它们各自 (x、y) 位置在获取、帧号和跟踪编号中。根据这些数据, 使用专用算法执行单元格分割和检测单元划分 (请参阅辅助代码文件)。另外两个文件被命名为 "跟踪统计信息" 和 "跟踪统计信息" 中的 "链接", 包括处理轨道的所有结果,例如跟踪工期、检测到的间隙数、跟踪初始帧等。</li>
	<li>使用单元格分割算法 (见补充码文件), 自动提取几个描述细胞形态学从重建阶段图像的指标。这些指标是细胞表面积, 细胞主轴长度 (l), 细胞小轴长度 (l) 和细胞长宽比 (l/升)。从无透镜显微镜中恢复的相位与前述15所讨论的试样层的密度和厚度成正比。</li>
	<li>除了细胞的形态学特征外, 从重建阶段13,19,20提取定量细胞干质量 (CDM) 测量结果 <img alt="Equation 1" src="/files/ftp_upload/56580/56580eq1v3.jpg">情商 (1) 其中φ (x, y) 是重构的相移19, λ波长和α = 1.8 x 10-4 m3/千克与折射率变化有关的特定折射率1, 19。</li>
	<li>用估计细胞折射率与培养基的差异来评估细胞厚度。20给出了单元格厚度h(x、y) 和测量的相移之间的关系: <img alt="Equation 2" src="/files/ftp_upload/56580/56580eq2v3.jpg">情商 (2.1) <img alt="Equation 3" src="/files/ftp_upload/56580/56580eq3v3.jpg">情商 (2.2) 使用Δn(x,y) = n单元格(x,y)- n中 (x,y), 单元格和区域性媒体之间的折射率差。在下面, 假定Δn = 0.025的常量值, 这是从在 HeLa 细胞核 (n = 1.35511) 和磷酸盐缓冲盐水 (PBS) 培养基 (n = 1.33) 中测量的折射率估计出来的。虽然细胞厚度值只是指示性的, 因为它是基于一个假设, 它的相对变化是有意义的, 可以利用来检测分裂细胞。</li>
	<li>使用专用算法 (请参阅辅助代码文件) 检测细胞分裂的发生, 然后提取与检测到的细胞分裂相关联的单元轨道, 以检测细胞分裂, 测量厚度大于8µm 的单元格。首先确定, 然后检查一个新的细胞是否在空间和时间紧密地出现。这样, 细胞分裂的检测依赖于两个健壮的标准。可替代的和更精细的细胞分裂检测方法可以应用到 lensfree 时间推移获取21,22,23。</li>
</ol>

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作者没有什么可透露的。

在本文中, 我们表明, 无透镜的视频显微镜可以在孵化器内使用, 以捕获数以千计的细胞的动力学。为了描述整个方法, 我们解释了如何用标准的细胞跟踪算法来分析2.7 天的 HeLa 细胞在培养中的时间推移获取。结果是一个具有 2.2 x 106单元格测量和10584个单元周期轨道的数据集。这项收购是对 Hela 细胞的一种文化进行的, 细胞间距离相对较大 (细胞密度 < 500 细胞/毫米2), 细胞形态学可以与圆盘近似。这两项功能便于应用自动单元跟踪分析, 从而可以收集如此大的数据集。其他细胞系较小的细胞间距离或更复杂的形貌将更难以跟踪和后续数据集将更小。
我们认为, 这种方法是有趣的许多研究, 例如细胞增殖和细胞大小的研究。后者是基础生物学研究的一个重要领域, 许多问题仍未得到解答, 如 Ginzberg et . 所述的很好的讨论。29. 在这项工作中提出的议定书因而提供了一种手段来衡量细胞增殖研究所需的重要指标, 即细胞周期持续时间、细胞干质量、末端与周期开始和细胞之间的细胞干质量比值。干质生长速率。除了对细胞增殖的研究外, 这种方法对细胞迁移的研究也很有兴趣, 因为它可以产生大量的轨道, 每一个持续数小时。本协议超越了艺术14、30的状态, 第一次演示了在10小时内获取数以千计的单元格轨道。
最后, 我们开发了一种易于使用的无透镜技术, 允许在数天的文化中同时跟踪数以千计的无标签细胞。

在几个细胞周期内监测培养的哺乳动物细胞, 准确测量细胞大小和细胞干质量是一项具有挑战性的任务。几个无标签的光学技术能够执行此任务1,2: 移相干涉测量3, 数字全息显微镜 (DHM)4,5,6,7, quadriwave 横向剪切干涉测量8,9和定量相断层扫描10,11。这些方法使人们对哺乳动物细胞周期的认识有了许多新的见解。然而他们很少加上自动细胞追踪算法, 并且他们的吞吐量仍然是有限的, 当测量细胞质量轨道1 (N < 20 分别在3,4,5,6). 因此, 需要用一种新的光学方法来测量大统计量 (N > 1000) 的细胞质量轨迹。
在本文中, 我们展示了无透镜视频显微镜的能力, 同时在孵化室内直接图像数以千计的细胞, 然后量化单个细胞指标沿数以千计的单个细胞周期轨道。无透镜显微镜是一种定量的相位成像技术, 它允许在一个非常大的视野 (通常数十毫米2, 这里29.4 毫米2)12,13 中获取密被包装细胞的相位图像. ,14,15。在单个单元格级别确定了几个度量值,例如、单元格区域、单元格的干质量、单元格粗细、单元格主轴长度和单元格长宽比12、15、每个图像。然后, 通过应用单元跟踪算法, 可以将这些功能绘制为每个单元格, 作为实验时间14、15的函数。此外, 通过检测细胞内的细胞分裂的发生, 有可能提取其他重要信息, 如初始细胞干质量 (刚刚细胞分裂), 最终细胞干质量 (刚刚细胞分裂) 和细胞周期持续时间,即, 两个连续的分区15之间的间隔。所有这些测量都可以计算出非常好的统计数据 (N > 1000), 因为大的视野通常允许分析200到1万细胞在一个单一的无透镜获取。
为了解释这种基于无透镜视频显微镜的方法, 我们描述了2.7 天内对 HeLa 细胞培养进行监测和量化的协议。数据分析是基于多波长全息重建、细胞跟踪、细胞分割和细胞分裂算法的四步过程。这里表明, 空间分辨率和相对较快的帧速率 (每10分钟一次采集) 获得与此无透镜视频显微镜设置兼容标准的细胞跟踪算法。对这个数据集的完整分析结果是在整个细胞周期内测量10584个细胞轨道。
总之, 无透镜视频显微镜是一个强大的工具, 自动监测数以千计的未标记, 不同步, 和未修改的细胞, 每个实验;在多个单元周期中跟踪每个单元格。因此, 我们的测量提供了几个细胞参数的平均值, 但更重要的是, 细胞间的变异超过了大量的细胞。

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			<td height="20" style="height:20px;width:231px;">Cytonote lens-free video microscope&#160;</td>
			<td style="width:208px;">Iprasense</td>
			<td style="width:156px;"></td>
			<td style="width:80px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Horus acquisition software</td>
			<td>Iprasense</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">6-well glass bottom culture plates</td>
			<td>MatTek corporation</td>
			<td>Part No: P06G-0-14-F&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DMEM + GlutaMAX medium&#160;</td>
			<td>Gibco</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">heat-inactivated fetal calf serum&#160;</td>
			<td>Eurobio</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">penicillin and streptomycin&#160;</td>
			<td>Gibco</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Fibronectin&#160;</td>
			<td>Sigma Aldrich</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Matlab, image processing toolbox&#160;</td>
			<td>Mathworks</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

lens-free video microscopy for the dynamic and quantitative analysis of adherent cell culture

在这里, 我们表明, 无透镜的视频显微镜, 使我们能够同时捕获数以千计的细胞的动力学, 直接在孵化器内, 并有可能监测和量化的单个细胞沿几个细胞周期。我们描述了用于监视和量化 HeLa 细胞培养2.7 天的完整协议。首先, 用无透镜的视频显微镜进行细胞培养, 然后在四步过程中分析数据: 多波长全息重建、细胞跟踪、细胞分割和细胞分裂检测算法.因此, 我们表明, 有可能收集具有超过1万个细胞周期轨道和超过 2 x 106细胞形态学测量的数据集。

Watch this Scientific Journal Video about Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture at JoVE.com

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

无透镜的视频显微镜使我们能够在孵化器内直接监测细胞培养。在这里, 我们描述了用于获取和分析2.7 天长时间获取培养的 HeLa 细胞的完整协议, 导致一个数据集 2.2 x 106测量单个细胞形态学和10584细胞周期轨道。

无透镜视频显微术在黏附细胞培养动态定量分析中的研究

Here, we demonstrate that lens-free video microscopy enables us to simultaneously capture the kinetics of thousands of cells directly inside the incubator ...

lens-free-video-microscopy-for-dynamic-quantitative-analysis-adherent

Nanyang Technological University

Research

JoVE Journal

Biology

9.4K 次观看.  Université Grenoble Alpes. 无透镜的视频显微镜使我们能够在孵化器内直接监测细胞培养。在这里, 我们描述了用于获取和分析2.7 天长时间获取培养的 HeLa 细胞的完整协议, 导致一个数据集 2.2 x 106测量单个细胞形态学和10584细胞周期轨道。

视频: Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

一个神经元和星形胶质细胞共培养检测神经毒性的高含量分析

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

科研

生物学

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software.  Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT.  To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images.  To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time.  The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.  

Video bioinformatics is the automated processing, analysis, understanding, and data mining of biological spatio-temporal data extracted from microscopic videos. The purpose of this article is to demonstrate a method for measuring human embryonic stem cell colony growth using a video bioinformatics method.

视频人类胚胎干细胞克隆生长的生物信息学分析

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer ...

Clonogenic Assay: Adherent Cells

The clonogenic (or colony forming) assay has been established for more than 50 years; the original paper describing the technique was published in 19561. Apart from documenting the method, the initial landmark study generated the first radiation-dose response curve for X-ray irradiated mammalian (HeLa) cells in culture1. Basically, the clonogenic assay enables an assessment of the differences in reproductive viability (capacity of cells to produce progeny; i.e. a single cell to form a colony of 50 or more cells) between control untreated cells and cells that have undergone various treatments such as exposure to ionising radiation, various chemical compounds (e.g. cytotoxic agents) or in other cases genetic manipulation. The assay has become the most widely accepted technique in radiation biology and has been widely used for evaluating the radiation sensitivity of different cell lines. Further, the clonogenic assay is commonly used for monitoring the efficacy of radiation modifying compounds and for determining the effects of cytotoxic agents and other anti-cancer therapeutics on colony forming ability, in different cell lines. A typical clonogenic survival experiment using adherent cells lines involves three distinct components, 1) treatment of the cell monolayer in tissue culture flasks, 2) preparation of single cell suspensions and plating an appropriate number of cells in petri dishes and 3) fixing and staining colonies following a relevant incubation period, which could range from 1-3 weeks, depending on the cell line. Here we demonstrate the general procedure for performing the clonogenic assay with adherent cell lines with the use of an immortalized human keratinocyte cell line (FEP-1811)2. Also, our aims are to describe common features of clonogenic assays including calculation of the plating efficiency and survival fractions after exposure of cells to radiation, and to exemplify modification of radiation-response with the use of a natural antioxidant formulation.

The applicability of the clonogenic assay for evaluating reproductive viability has been established for more than 50 years. Here we demonstrate the general procedure for performing the clonogenic assay with adherent cells.

克隆形成含量:贴壁细胞

The clonogenic (or colony forming) assay has been established for more than 50 years; the original paper describing the technique was published in 19561. ...

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using fluorochromes like Green Fluorescent Protein (GFP) directly attached to the protein of interest has become increasingly popular 1. Using GFP and similar fluorochromes the subcellular localisations and movements of proteins can be detected in a fluorescent microscope. Moreover, also the subnuclear localisation of a certain region of a chromosome can be studied using this technique. GFP is fused to the Lac Repressor protein (LacR) and ectopically expressed in the cell where tandem repeats of the lacO sequence has been inserted into the region of interest on the chromosome2. The LacR-GFP will bind to the lacO repeats and that area of the genome will be visible as a green dot in the fluorescence microscope. Yeast is especially suited for this type of manipulation since homologous recombination is very efficient and thereby enables targeted integration of the lacO repeats and engineered fusion proteins with GFP 3. Here we describe a quantitative method for live cell analysis of fission yeast. Additional protocols for live cell analysis of fission yeast can be found, for example on how to make a movie of the meiotic chromosomal behaviour 4. In this particular experiment we focus on subnuclear organisation and how it is affected during gene induction. We have labelled a gene cluster, named Chr1, by the introduction of lacO binding sites in the vicinity of the genes. The gene cluster is enriched for genes that are induced early during nitrogen starvation of fission yeast 5. In the strain the nuclear membrane (NM) is labelled by the attachment of mCherry to the NM protein Cut11 giving rise to a red fluorescent signal. The Spindle Pole body (SPB) compound Sid4 is fused to Red Fluorescent Protein (Sid4-mRFP) 6. In vegetatively growing yeast cells the centromeres are always attached to the SPB that is embedded in the NM 7. The SPB is identified as a large round structure in the NM. By imaging before and 20 minutes after depletion of the nitrogen source we can determine the distance between the gene cluster (GFP) and the NM/SPB. The mean or median distances before and after nitrogen depletion are compared and we can thus quantify whether or not there is a shift in subcellular localisation of the gene cluster after nitrogen depletion.

The fission yeast, Schizosaccharomyces pombe, is a good model system to study basic cellular processes. Here we describe a method to perform quantitative live cell analysis of fission yeast. In this particular experiment we focus on organisation of the genome within the cell nucleus, but the method can also be used to study cytosolic factors.

裂殖酵母的活细胞定量荧光显微镜分析

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

随机使用时移视频显微镜细胞迁移的定量分析

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

A Quantitative Fitness Analysis Workflow

Quantitative Fitness Analysis (QFA) is an experimental and computational workflow for comparing fitnesses of microbial cultures grown in parallel1,2,3,4. QFA can be applied to focused observations of single cultures but is most useful for genome-wide genetic interaction or drug screens investigating up to thousands of independent cultures. The central experimental method is the inoculation of independent, dilute liquid microbial cultures onto solid agar plates which are incubated and regularly photographed. Photographs from each time-point are analyzed, producing quantitative cell density estimates, which are used to construct growth curves, allowing quantitative fitness measures to be derived. Culture fitnesses can be compared to quantify and rank genetic interaction strengths or drug sensitivities. The effect on culture fitness of any treatments added into substrate agar (e.g. small molecules, antibiotics or nutrients) or applied to plates externally (e.g. UV irradiation, temperature) can be quantified by QFA.
The QFA workflow produces growth rate estimates analogous to those obtained by spectrophotometric measurement of parallel liquid cultures in 96-well or 200-well plate readers. Importantly, QFA has significantly higher throughput compared with such methods. QFA cultures grow on a solid agar surface and are therefore well aerated during growth without the need for stirring or shaking.
QFA throughput is not as high as that of some Synthetic Genetic Array (SGA) screening methods5,6. However, since QFA cultures are heavily diluted before being inoculated onto agar, QFA can capture more complete growth curves, including exponential and saturation phases3. For example, growth curve observations allow culture doubling times to be estimated directly with high precision, as discussed previously1.
Here we present a specific QFA protocol applied to thousands of S. cerevisiae cultures which are automatically handled by robots during inoculation, incubation and imaging. Any of these automated steps can be replaced by an equivalent, manual procedure, with an associated reduction in throughput, and we also present a lower throughput manual protocol. The same QFA software tools can be applied to images captured in either workflow.
We have extensive experience applying QFA to cultures of the budding yeast S. cerevisiae but we expect that QFA will prove equally useful for examining cultures of the fission yeast S. pombe and bacterial cultures.

Quantitative Fitness Analysis (QFA) is a complementary series of experimental and computational methods for estimating microbial culture fitnesses. QFA estimates the effect of genetic mutations, drugs or other applied treatments on microbe growth. Experiments scaling from focussed analysis of single cultures to thousands of parallel cultures can be designed.

定量健身分析工作流程

Quantitative Fitness Analysis (QFA) is an experimental and computational workflow for comparing fitnesses of microbial cultures grown in parallel1,2,3,4. ...

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, traditional chemotherapeutic approaches have been largely unsuccessful. Hormone therapy is effective at early stage, but often fails with the eventual development of hormone-refractory tumors. We have been interested in developing therapeutics targeting specific metabolic deficiency of tumor cells. We recently showed that prostate tumor cells specifically lack an enzyme (argininosuccinate synthase, or ASS) involved in the synthesis of the amino acid arginine1. This condition causes the tumor cells to become dependent on exogenous arginine, and they undergo metabolic stress when free arginine is depleted by arginine deiminase (ADI)1,10. Indeed, we have shown that human prostate cancer cells CWR22Rv1 are effectively killed by ADI with caspase-independent apoptosis and aggressive autophagy (or macroautophagy)1,2,3. Autophagy is an evolutionarily-conserved process that allows cells to metabolize unwanted proteins by lysosomal breakdown during nutritional starvation4,5. Although the essential components of this pathway are well-characterized6,7,8,9, many aspects of the molecular mechanism are still unclear - in particular, what is the role of autophagy in the death-response of prostate cancer cells after ADI treatment? In order to address this question, we required an experimental method to measure the level and extent of autophagic response in cells - and since there are no known molecular markers that can accurately track this process, we chose to develop an imaging-based approach, using quantitative 3D fluorescence microscopy11,12.
Using CWR22Rv1 cells specifically-labeled with fluorescent probes for autophagosomes and lysosomes, we show that 3D image stacks acquired with either widefield deconvolution microscopy (and later, with super-resolution, structured-illumination microscopy) can clearly capture the early stages of autophagy induction. With commercially available digital image analysis applications, we can readily obtain statistical information about autophagosome and lysosome number, size, distribution, and degree of colocalization from any imaged cell. This information allows us to precisely track the progress of autophagy in living cells and enables our continued investigation into the role of autophagy in cancer chemotherapy.

Autophagy is a ubiquitous process that enables cells to degrade and recycle proteins and organelles. We apply advanced fluorescence microscopy to visualize and quantify the small, but essential, physical changes associated with the induction of autophagy, including the formation and distribution of autophagosomes and lysosomes, and their fusion into autolysosomes.

采用先进的3D荧光显微镜定量分析自噬

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, ...

Analysis of the Gap Junction-dependent Transfer of miRNA with 3D-FRAP Microscopy

Small antisense RNAs, like miRNA and siRNA, play an important role in cellular physiology and pathology and, moreover, can be used as therapeutic agents in the treatment of several diseases. The development of new, innovative strategies for miRNA/siRNA therapy is based on an extensive knowledge of the underlying mechanisms. Recent data suggest that small RNAs are exchanged between cells in a gap junction-dependent manner, thereby inducing gene regulatory effects in the recipient cell. Molecular biological techniques and flow cytometric analysis are commonly used to study the intercellular exchange of miRNA. However, these methods do not provide high temporal resolution, which is necessary when studying the gap junctional flux of molecules. Therefore, to investigate the impact of miRNA/siRNA as intercellular signaling molecules, novel tools are needed that will allow for the analysis of these small RNAs at the cellular level. The present protocol describes the application of three-dimensional fluorescence recovery after photobleaching (3D-FRAP) microscopy to elucidating the gap junction-dependent exchange of miRNA molecules between cardiac cells. Importantly, this straightforward and non-invasive live-cell imaging approach allows for the visualization and quantification of the gap junctional shuttling of fluorescently labeled small RNAs in real time, with high spatio-temporal resolution. The data obtained by 3D-FRAP confirm a novel pathway of intercellular gene regulation, where small RNAs act as signaling molecules within the intercellular network.

Here, we describe the application of three-dimensional fluorescence recovery after photobleaching (3D-FRAP) for the analysis of the gap junction-dependent shuttling of miRNA. In contrast to commonly applied methods, 3D-FRAP allows for the quantification of the intercellular transfer of small RNAs in real time, with high spatio-temporal resolution.

用3D-FRAP显微镜分析miRNA的间隙连接依赖性转移

Small antisense RNAs, like miRNA and siRNA, play an important role in cellular physiology and pathology and, moreover, can be used as therapeutic agents ...

Oligomerization Dynamics of Cell Surface Receptors in Living Cells by Total Internal Reflection Fluorescence Microscopy Combined with Number and Brightness Analysis

Despite the importance and ubiquity of receptor oligomerization, few methods are applicable for detecting clustering events and measuring the degree of clustering. Here, we describe an imaging approach to determine the average oligomeric state of mEGFP-tagged-receptor homocomplexes in the membrane of living cells. The protocol is based on Total Internal Reflection Fluorescence (TIRF) microscopy combined with Number and Brightness (N&#38;B) analysis. N&#38;B is a method similar to fluorescence-correlation spectroscopy (FCS) and photon counting histogram (PCH), which are based on the statistical analysis of the fluctuations of the fluorescence intensity of fluorophores diffusing in and out of an illumination volume during an observation time. In particular, N&#38;B is a simplification of PCH to obtain information on the average number of proteins in oligomeric mixtures. The intensity fluctuation amplitudes are described by the molecular brightness of the fluorophore and the average number of fluorophores within the illumination volume. Thus, N&#38;B considers only the first and second moments of the amplitude distribution, namely, the mean intensity and the variance. This is, at the same time, the strength and the weakness of the method. Because only two moments are considered, N&#38;B cannot determine the molar fraction of unknown oligomers in a mixture, but it only estimates the average oligomerization state of the mixture. Nevertheless, it can be applied to relatively small time series (compared to other moment methods) of images of live cells on a pixel-by-pixel basis, simply by monitoring the time fluctuations of the fluorescence intensity. It reduces the effective time-per-pixel to a few microseconds, allowing acquisition in the time range of seconds to milliseconds, which is necessary for fast oligomerization kinetics. Finally, large cell areas as well as sub-cellular compartments can be explored.

We describe an imaging approach for the determination of the average oligomeric state of mEGFP-tagged-receptor oligomers induced by ligand binding in the plasma membrane of living cells. The protocol is based on Total Internal Reflection Fluorescence (TIRF) microscopy combined with Number and Brightness (N&#38;B) analysis.

通过总内部反射荧光显微镜与数量和亮度分析相结合，活细胞中细胞表面受体的显微化动力学

Despite the importance and ubiquity of receptor oligomerization, few methods are applicable for detecting clustering events and measuring the degree of ...

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out shape. Following the cell-substrate attachment, the cell forms a thin sheet of lamellipodia emanating from the cell body. In the lamellipodia, globular actin (G-actin) monomers polymerize into a dense filamentous actin (F-actin) meshwork that pushes against the plasma membrane, thereby providing the mechanical forces required for the cell to spread. Notably, the molecular players that control the actin polymerization in lamellipodia are essential for many other cellular processes, such as cell migration and endocytosis. 
Since spreading cells form continuous lamellipodia that span the entire cell periphery and persistently expand outward, cell spreading assays have become an efficient tool to assess the kinetics of lamellipodial protrusions. Although several technical implementations of the cell spreading assay have been developed, a detailed description of the workflow, which would include both a step-by-step protocol and computational tools for data analysis, is currently lacking. Here, we describe the experimental procedures of the cell spreading assay and present an open-source tool for quantitative and unbiased analysis of cell edge dynamics during spreading. When combined with pharmacological manipulations and/or gene-silencing techniques, this protocol is amenable to a large-scale screen of molecular players regulating lamellipodial protrusions.

In this protocol, we present the experimental procedures of a cell spreading assay that is based on live-cell microscopy. We provide an open-source computational tool for the unbiased segmentation of fluorescently labeled cells and quantitative analysis of lamellipodia dynamics during cell spreading.

细胞扩散过程中细胞边缘动力学的定量分析

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out ...