Name: characterization of in vitro differentiation of human primary keratinocytes by rna-seq analysis
Uploaded: 2020-05-16T13:00:00
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这项研究得到了荷兰科学研究组织的支持（NWO/ALW/MEERVOUD/836.12.010，H.Z.）（NWO/ALW/公开竞争/ALWOP 376，H.Z.，J.G.A.S.）;拉德布德大学奖学金（H.Z.）;和中国奖学金委员会助学金201406330059（J.Q.）。

皮肤活检取自健康志愿者或p63突变患者的躯干，以建立原发性角蛋白细胞培养。关于建立人类原生角蛋白细胞的所有程序都得到拉德布德大学尼梅根医疗中心伦理委员会的批准（"门斯格邦登·翁德佐克·阿纳姆-尼梅根"）。已获得知情同意。
1. 通过接触抑制，人类原发性角蛋白细胞分化
<ol><li>必要时从角蛋白细胞基质（材料表）中准备角蛋白细胞生长介质（KGM）...

<ol>
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本工作描述了一种利用RNA-seq分析诱导人类角蛋白细胞分化和后续表征的方法。在目前的文献中，许多关于人类角蛋白细胞分化的研究使用另外两种方法，高钙浓度或以血清作为诱导分化的方法2，3，23。前一份报告仔细比较了这三种不同的方法3，表明这些方法可以代表角蛋白细胞分化的不同生物学。在同一份...

人类原发性角蛋白细胞来源于人类皮肤，常被用作细胞模型，研究表皮1、2、3、4的生物学。表皮的分层可以通过角蛋白细胞分化进行建模，无论是2D水下单层方式，还是3D空气提升器官模型2、3、5、6、7。虽然 3D 模型在评估表皮结构和功能方面变得越来越重要，但由于 2D 分化模型的便利性和生成大量用于分析的细胞的可能性，因此仍然广泛使用。
各种条件已应用于诱导角蛋白细胞分化的2D，包括血清的添加，高浓度的钙，较低的温度和抑制表皮生长因子受体2，3。这些方法中的每一个方法都经过了许多角蛋白细胞分化标记基因的验证，并证明在评估角蛋白细胞分化（包括在病理条件下）是有效的。然而，当对标记基因的特定面板进行2、3的检查时，这些诱导条件也显示了其分化效率和动力学的差异。
其中一种方法涉及角蛋白细胞接触抑制和消耗生长因子在培养媒介8。研究表明，当细胞达到全密度时，角蛋白细胞可以自发分化。 将文化媒介中的增长因素排除在外，可以进一步增强差异化。将接触抑制和减损生长因子相结合的方法已被证明在使用多个表皮标记3时，产生具有与正常分层表皮相似的基因表达模式的分化角蛋白细胞，表明该模型适合研究正常的角蛋白细胞分化。最近，利用该模型对角蛋白细胞分化进行了两次综合基因表达分析，结果报告了9、10。研究人员在分子水平上验证了该模型，并表明它可用于研究正常和患病的角蛋白细胞分化。
本协议描述了使用RNA-seq进行体外分化方法和分化细胞分子分析的过程。它还说明了分化日（增殖阶段）、第2天、第4天和第7天（分别早期、中间和晚期分化）细胞转录组的特点。表明，分化的角蛋白细胞显示基因表达模式，在表皮分层期间，它们与细胞大体相似。为了研究这种方法是否可用于研究皮肤病理学，我们应用了相同的实验和分析管道，以研究携带转录因子p63突变的角蛋白细胞，这些突变来自结膜、异体发育不良和唇裂（EEC）综合征11，12的患者。该协议侧重于角蛋白细胞的体外分化以及随后对RNA-seq的生物信息学分析。完整程序的其他步骤，如RNA提取、RNA-seq样品制备和库结构，都记录得很好，很容易遵循，尤其是在使用许多常用商业试剂盒时。因此，这些步骤仅在协议中简要说明。数据表明，该管道适用于研究健康与患病角细胞表皮分化期间的分子事件。

<table border="0" cellpadding="0" cellspacing="0" style="width:892px;" width="892">
	<colgroup>
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	</colgroup>
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:397px;">Bioanalyzer 2100</td>
			<td style="width:231px;">Agilent</td>
			<td style="width:200px;">G2929BA</td>
			<td style="width:64px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Bovine pituitary extract (BPE)</td>
			<td>Lonza</td>
			<td></td>
			<td>Part of the bulletKit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">CFX96 Real-Time system</td>
			<td>Bio-Rad</td>
			<td></td>
			<td>qPCR machine</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dulbecco&#39;s Phosphate-Buffered Saline (DPBS)</td>
			<td>Sigma-Aldrich</td>
			<td>D8537</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Epidermal Growth Factor (EGF)</td>
			<td>Lonza</td>
			<td></td>
			<td>Part of the bulletKit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ethanolamine &#62;= 98%</td>
			<td>Sigma-Aldrich</td>
			<td>E9508</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">High Sensitivity DNA chips</td>
			<td>Agilent</td>
			<td>5067-4626</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Hydrocortison</td>
			<td>Lonza</td>
			<td></td>
			<td>Part of the bulletKit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Insulin</td>
			<td>Lonza</td>
			<td></td>
			<td>Part of the bulletKit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">iQ SYBR Green Kit</td>
			<td>BioRad</td>
			<td>170-8886</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">iScript cDNA synthesis</td>
			<td>Bio rad</td>
			<td>1708890</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">KAPA Library Quant Kit</td>
			<td>Roche</td>
			<td>07960255001</td>
			<td>Low concentration measure kit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">KAPA RNA HyperPrep Kit with RiboErase</td>
			<td>Roche</td>
			<td>KK8540</td>
			<td>RNAseq kit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">KGM Gold Keratinocyte Growth Medium BulletKit</td>
			<td>Lonza</td>
			<td>192060</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nanodrop</td>
			<td>deNovix</td>
			<td>DS-11 FX (model)</td>
			<td>Nanodrop and Qbit for DNA and RNA measurements</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">NEXTflex DNA barcodes -24</td>
			<td>Illumnia</td>
			<td>NOVA-514103</td>
			<td>6 bp long primers</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Penicillin-Streptomycin</td>
			<td>Gibco</td>
			<td>15140122</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNA Pico Chip</td>
			<td>Agilent</td>
			<td>5067-1513</td>
			<td></td>
		</tr>
	</tbody>
</table>

characterization of in vitro differentiation of human primary keratinocytes by rna-seq analysis

人类原发性角蛋白细胞经常用作体外模型，用于表皮分化和相关疾病的研究。报告了利用各种诱导条件以二维（2D）水下方式培养的角蛋白细胞体外分化的方法。这里描述的是2D体外角细胞分化方法通过接触抑制和随后的分子表征RNA-seq的过程。简言之，角蛋白细胞生长在定义的角蛋白细胞介质中，辅以生长因子，直到它们完全汇合。分化是由角蛋白细胞之间的密切接触引起的，并因排除介质中的生长因子而进一步刺激。利用RNA-seq分析，发现1）分化的角蛋白细胞在分化过程中表现出不同的分子特征，2）动态基因表达模式在表皮分层期间与细胞大体相似。至于与正常角蛋白细胞分化的比较，携带转录因子p63突变的角蛋白细胞表现出改变的形态和分子特征，符合其分化缺陷。最后，本协议详细介绍了2D体外角细胞分化的步骤及其分子特征，重点是RNA-seq数据的生物信息学分析。由于RNA提取和RNA-seq程序有据可查，因此它不是本协议的重点。体外角蛋白细胞分化的实验程序及生物信息分析管道可用于研究健康与患病角蛋白细胞表皮分化期间的分子事件。

正常角蛋白细胞分化和RNA-seq分析 在这个实验中，从五个个体中提取的角蛋白细胞线用于分化和RNA-seq分析。图1总结了分化的实验过程和RNA-seq分析结果。图1A中显示了正常角蛋白细胞的体外分化过程和分化过程中细胞形态变化的概述。原理成分分析（PCA）显示，接受分化的角蛋白细胞具有连接但独特的整体基因表达特征（?...

Watch this Scientific Journal Video about Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis at JoVE.com

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

这里介绍的是一个逐步的过程，通过接触抑制来分离人类原性角蛋白细胞的体外分化，然后通过RNA-seq分析在分子水平上进行表征。

通过RNA-Seq分析，人类原主角细胞的体外分化特征

Human primary keratinocytes are often used as in vitro models for studies on epidermal differentiation and related diseases. Methods have been reported ...

在此协议中，我们描述了一个包含两个部分的过程。首先，单层2D角蛋白细胞分化方法在体外通过接触抑制。其次，其分子特征由RNA-seq。2D 体外分化方法简单易用。它可用于研究表皮分化，特别是当大量的细胞是必要的。例如，在表观分析中。详细的RNA-seq分析管道对于具有基本生物信息学技能的研究人员来说是清晰透明的，可用于任何散装RNA-seq分析。首次执行分化协议时，请记住，播种密度可能比较棘手。尝试多个种子密度，找出哪一个最适合您的细胞系。首先根据手稿方向制备角蛋白细胞生长介质或 KGM 和 500 毫升增殖介质和分化介质。种子原发性角蛋白细胞密度为每厘米5至2万细胞，并添加足够的增殖介质来覆盖细胞。播种两天后，用增殖介质刷新细胞。在显微镜下定期检查细胞，每隔一天刷新一次。当细胞达到90%汇合时，通过改变介质到分化介质来诱导分化。要收集细胞以进行进一步的RNA分析，用DPBS清洗细胞两次，然后加入解解缓冲液。在分化日零、二、四和七收集细胞。RNA分离后，双链cDNA将被转换，RNA-seq库将为下一代测序做好准备。测序后，序列读取将被下载并映射到人类基因组。下载并安装 R 包后，从 readspergene.out 生成帐户表。选项卡文件并编写包含所有文件名、区分日和其他相关示例数据的示例数据文件。有关示例，请参阅补充编码文件。然后使用计数表和示例数据生成包含可计数和示例数据的 deseq2 对象。对于基因表达规范化，使用 deseq2RLD 或 VST 规范化 deseq2 对象中的计数表。虽然 RLD 规范化是首选，但 VST 规范化要快得多。使用 R 中的 dist 函数根据规范化的读取计数强度绘制样本距离，然后根据样本距离执行 hclust 聚类。接下来，使用 pheatmap 函数绘制热图。最后，使用 deeq2 的绘图 PCA 函数生成规范化读取计数强度的原理分量分析或 PCA 图。PCA 是探索性数据分析的工具，可用于可视化不同样本之间的距离和连接。使用 rowVars 函数执行高度可变的基因表达分析，该函数通过按不同时间点样本之间的方差顺序提取前 500 个高度可变基因。这些基因在分化日中其标准化强度的标准偏差最高。对高度可变的基因执行 k-means 聚类，通过不同的表达式模式对它们进行聚类。使用图图包在热图中可视化基因。热图中绘制的强度是除去 2 规范化强度，减去中值。生成一个表达背景基因的列表，包括单个样本中计数超过 10 个的所有基因，并列出每个组的基因。最后，使用GOrilla执行基因本体分析。使用背景基因列表作为背景集，将集群中高度可变基因列表用作目标集，然后单击搜索丰富的 GO 术语。或者，更高级的 R 用户可以使用包群集Profiler自动执行 GO 术语扩充分析。在RNA-seq分析中，从5个个体中提取的角蛋白细胞线用于分化。主要成分分析表明，经过分化的角蛋白细胞具有连接但独特的整体基因表达特征。高度可变的基因聚集在一起，以可视化分化过程中的基因表达动力学和模式。每个基因组都以角蛋白细胞分化特征基因表示，基因本体论注释显示出基因功能的显著差异。在第二个实验中，比较了来自健康对联的角蛋白细胞和来自携带P63突变的患者的细胞系之间的细胞形态和基因表达差异。主要成分分析表明，控制细胞系明显遵循分化模式，但分化过程中突变细胞的基因表达模式与增殖或未分化细胞的基因表达模式基本相似。在聚类分析中，聚类一中的基因在控制细胞中受到降低控制，在携带R204W和R279H突变的患者细胞中部分降低调节，但在携带R304W的细胞中保持高。如基因本体分析所示，这些基因可能在细胞增殖中发挥作用。两个基因集群首先被引入，随后在控制细胞中降低调节。这些基因很可能参与角蛋白细胞分化，因为表皮分化和角蛋白化功能在这个集群中具有高度丰富性。第三组的基因仅在控制细胞分化结束时诱导，这表明它们可能在表皮的最外层发挥作用。在分析RNA-seq数据时，事先了解预期结果非常重要。这将帮助你解释质量控制和 PCA 图，并评估您的结果是否有意义。我们的方法可用于研究表皮生物学和其他生物系统中的基因转录。

Research

JoVE Journal

Genetics

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

在人原代细胞培养生物钟基因表达及荷尔蒙分泌的并行测量

Circadian clocks are functional in all light-sensitive organisms, allowing for an adaptation to the external world by anticipating daily environmental ...

科研

遗传学

Analysis of the Ambient Particulate Matter-induced Chromosomal Aberrations Using an In Vitro System

Analysis of the Ambient Particulate Matter-induced Chromosomal Aberrations Using an In Vitro System

使用了大气颗粒物引起的染色体畸变分析<em&gt;体外</em&gt;系统

Exposure to particulate matter (PM) is a major world health concern, which may damage various cellular components, including the nuclear genetic material. ...

Analysis of Cap-binding Proteins in Human Cells Exposed to Physiological Oxygen Conditions

暴露在生理条件下的氧气在人体细胞中帽结合蛋白质分析

Translational control is a focal point of gene regulation, especially during periods of cellular stress. Cap-dependent translation via the eIF4F complex ...

Genome Editing and Directed Differentiation of hPSCs for Interrogating Lineage Determinants in Human Pancreatic Development

基因组编辑和hPSCs定向分化为胰腺癌发展讯问谱系行列式

Interrogating gene function in self-renewing or differentiating human pluripotent stem cells (hPSCs) offers a valuable platform towards understanding ...

Kinetics of Lagging-strand DNA Synthesis In Vitro by the Bacteriophage T7 Replication Proteins

Kinetics of Lagging-strand DNA Synthesis In Vitro by the Bacteriophage T7 Replication Proteins

滞后链DNA合成的动力学研究<em&gt;体外</em&gt;由T7噬菌体复制蛋白

Here we provide protocols for the kinetic examination of lagging-strand DNA synthesis in vitro by the replication proteins of bacteriophage T7. The T7 ...

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

ATAC 基因组在原发性人类 T 淋巴细胞中的染色体全易接近染色质

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions ...

Differentiation, Maintenance, and Analysis of Human Retinal Pigment Epithelium Cells: A Disease-in-a-dish Model for BEST1 Mutations

Differentiation, Maintenance, and Analysis of Human Retinal Pigment Epithelium Cells: A Disease-in-a-dish Model for BEST1 Mutations

人视网膜色素上皮细胞的分化、维持和分析: 一种BEST1突变的碟形模型

Although over 200 genetic mutations in the human BEST1 gene have been identified and linked to retinal degenerative diseases, the pathological mechanisms ...

Isolation, Characterization and MicroRNA-based Genetic Modification of Human Dental Follicle Stem Cells

人牙小泡干细胞的分离、鉴定及微 rna 遗传修饰

To date, several stem cell types at different developmental stages are in the focus for the treatment of degenerative diseases. Yet, certain aspects, such ...

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

人类胰腺胰岛的单细胞RNA测序与分析

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to ...

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

改进小RNA-seq：减少偏差，更好地检测2'-O-甲基RNA

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNA such as ...