这项工作得到了 NIH 的资助, 包括来自研究院、R01HG008135 和 NHGRI 的 DP1HD087990。我们感谢中实验室的成员有价值的反馈。
作者投稿: X.C. 和 A.T.Z. 更新 GeNemo 通过编码新的接口和特点;A.T.Z. 制作了 in-house 样品视频;A.T.Z., 十° C 和深圳写了这篇论文。

注意: 协议可以在任何地方暂停. 
 1. 基本设置 <ol> <li> 获取包含要输入到基因组中的数据的床、峰值格式或要人 7 文件。该文件应具有扩展名和 #34; 床和 #34;, #34; broadpeaks 和 #34; #34; narrowpeaks 和 #34; 或 #34; 要人和 #34; 分别. 
	#8203; 注意: 这些类型的文件的 zip 版本也将工作. </li>
	<li> 使用 internet 浏览器转到 genemo.org。任何能够运行最常见的互联网浏览器的操作系统都应该能够使用 GeNemo. 
	<ol> <li> 使用下拉菜单选择要搜索的物种。目前可用的物种包括人类和老鼠. </li>
		<li> 使用 url 或直接上载上传用户文件。要人文件只使用 url 上传方法。床和峰格式文件与两种方法一起使用 (摆动文件不能作为主数据上载到现在). </li>
	</ol> </li> </ol> 2。可选设置 <ol> <li> 在相应的框中提供电子邮件地址, 以便在搜索完成时通过电子邮件接收搜索结果. 
	#8203; 注意: 当搜索大部分的基因组和/或反对大量的轨道 (见下文), 建议用户提供他/她的电子邮件, 因为搜寻可能需要很长的时间。例如, 100 megabase 搜索大约需要十五年代。搜索结果的链接将被发送到搜索完成时提供的电子邮件地址。链接将在搜索完成后的7天内过期. </li>
	<li> 提供要人文件或摆动显示文件可能来自 url。这个显示文件不会影响结果;它只会显示在结果旁边. </li>
	<li> 在相应的框中指定搜索范围 (包括染色体和基对位置). 
	<ol> <li> 列出染色体、起始基对和结束基对. </li>
		<li> 使用和 #39; 宥和 #39; 对于染色体格式, 在哪里和 #39; N 和 #39; 是染色体号/字母 (1、2和 #8230; X 或 Y)。对于基对, 只需键入数字. </li>
		<li> 在所有三项之间包含空格, 或包括冒号 (:) 在染色体编号和第一个基对之间, 和/或两个基对之间的连字符。例如: chr1:1000000-2000000, chr1 1000000 2000000, chr1 1000000-2000000, chr1:1000000 2000000. 
		注意: 步骤 2.1-2.3 是可选的. </li>
	</ol> </li> </ol> <img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56136/56136fig1.jpg"/> 图 1 : GeNemo 和 #39 的首页, 并填写了所需的区域. 和 #160; 用户需要输入的物种, 搜索文件和搜索范围, 并选择轨道, 他/她希望搜索。电子邮件地址和显示文件是可选的. #160; <a href="//ecsource.jove.com/files/ftp_upload/56136/56136fig1large.jpg" target="_blank"> 请单击此处查看此图的较大版本. </a> 
 3. 数据选择 <img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56136/56136fig2.jpg"/> 图 2 : 跟踪选择窗口. #160; 这是通过单击 #34;D ata 选择和 #34; 首页上的按钮来提出的。在这里, 用户可以选择跟踪来搜索输入文件。某些曲目在默认情况下已被选中. #160; <a href="//ecsource.jove.com/files/ftp_upload/56136/56136fig2large.jpg" target="_blank"> 请单击此处查看此图的较大版本. </a> 
<ol> <li> 单击数据选择按钮后, 选择要搜索的曲目类型 ( (即 ), 以添加到查询中)。跟踪收集包括来自世界各地实验室的许多不同的数据集. 
	<ol> <li> 由于曲目列表很长, 用户可能需要使用 "滤镜" 按钮 (在顶部) 以方便跟踪选择。轨道可以通过实验、组织、细胞系和/或实验室进行过滤. </li>
		<li> 底部有五按钮可帮助执行跟踪选择: 全选、无选择、添加、筛选、排除. </li>
		<li> 选择所有和 #34; 和 #34; 选择 "无" 和 #34; 不言自明. </li>
		<li> #34; 添加和 #34; 按钮将当前选定的曲目添加到查询中。它充当逻辑门和 #34; 或 #34;。请注意, 选择上面的筛选器 ( 例如 、某些实验、组织、单元格线或实验室) 不会自动向搜索查询中添加相应的跟踪。用户必须首先选择曲目 ( 如 , 脑, 肝组织下), 然后单击 #34; 添加和 #34; 按钮将它们添加到查询中。选择曲目时, 请注意, 只有在 "筛选" 窗口的 "打开" 选项卡中指定的筛选器才会应用于搜索查询。其他选项卡上的选择将保存在 "筛选" 窗口中, 但不应用于搜索查询. </li>
		<li> "#34; 筛选器和 #34;" 按钮只保留查询中当前选定的轨道类型, 并删除所有其他类型的曲目。它充当逻辑门和 #34; 和 #34;。基本上, #34; 过滤器和 #34; 允许选择两个类别的轨道之间的交互 ( 例如 , 特定实验室的某些组织)。请注意, #34; 筛选器和 #34; 如果查询中尚未存在所选的曲目类型, 则不会将其添加到 query 中. </li>
		<li> "#34; 排除和 #34;" 按钮将从查询中删除当前在筛选器窗口中选定的所有类型的曲目。它充当逻辑门和 #34; 不 #34;, 反对和 #34; 过滤器和 #34; 功能。再次, #34; 排除和 #34; 不将当前未在筛选器窗口中选择的任何曲目添加到查询中. </li>
	</ol> </li> </ol> <img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56136/56136fig3.jpg"/> 图 3 : 筛选器窗口.这是通过点击和 #34, 过滤器和 #34, 在轨道选择窗口按钮。在这里, 用户可以同时选择多个曲目, 相对轻松. #160; <a href="//ecsource.jove.com/files/ftp_upload/56136/56136fig3large.jpg" target="_blank"> 请单击此处查看此图的较大版本. </a> 
 <img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56136/56136fig4.jpg"/> 图 4 : 如何使用筛选器函数 。#160; <a href="//ecsource.jove.com/files/ftp_upload/56136/56136fig4large.jpg" target="_blank"> 请单击此处查看此图的较大版本. </a> 
<ol start="2"> <li> 在将所需的曲目添加到查询后, 单击 "#34; 更新和 #34; 右下角的按钮。为了适应两种选择数据的方法: 选择单个数据跟踪或筛选/排除, 这是必需的。#34; 重置视图和 #34; 按钮将查询重置为与人类/小鼠胚胎干细胞基因表达调控相关的默认轨道. 
	注意: 选择要通过和 #34;D ata 选择和 #34 进行搜索的曲目; 是可选的, 但建议使用因为默认的搜索曲目很可能不适合用户和 #39 的需求. </li>
</ol> 4。搜索和结果 <ol> <li> 在数据选择之后单击和 #34; 搜索和 #34; 按钮。搜索可能需要一些时间. </li>
	<li> 搜索完成后, 用户将在结果页中看到各种框。每个框代表一个部分的基因组, 其中一个用户和 #39; s 数据文件与一个或多个用户查询的轨道有一个紧密匹配的模式. 
	<ol> <li> 如果没有可见的框, 请尝试搜索更多类型的曲目, 或使用相同的输入文件使搜索范围更大。一个简单的方法来做到这一点, 没有重做的一切是点击 #34; #9776 #34; 按钮旁边的标志。这将打开一个允许用户修改搜索的边栏. </li>
		<li> 结果可以通过单击 #34;D ownload 床文件和 #34, 然后在结果页底部的按钮上导出为床文件. </li>
	</ol> </li> <li> 单击每个框右上的 "可视化" 按钮以直观显示结果. 
	<ol> <li> 在右侧的可视化面板中, 将显示多个内容, 包括数据 (包含用户输入文件)、输入的显示文件、匹配的曲目和某些默认轨道。从结果中, 用户可以将已知的编码数据集与所提供的数据集进行比较, 以进行进一步的调查。用户也可以参考 UCSC 基因来查看查询结果的上下文。如果选择来自多个细胞系/组织的轨道, 用户可以使用这样的结果来了解给定数据集和编码数据集之间的相似性的组织特异性. </li>
		<li> 在结果页上, 用户可以在任何轨道上拖动以移动基因组的上游或下游; 当鼠标光标位于坐标上时, 用户可以使用鼠标滚轮和/或放大和缩小. </li>
	</ol> </li> </ol> <img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56136/56136fig5.jpg"/> 图 5 : 结果页 。此特定搜索返回363匹配区域。显示第一个匹配区域可以通过单击 "#34"、"显示和 #34"、"每个结果区域" 框左下角的按钮来完成。在显示窗口的左侧部分可以看到, 两个数据文件 (输入和选择的轨道) 在信号强度模式上是相似的. #160; <a href="//ecsource.jove.com/files/ftp_upload/56136/56136fig5large.jpg" target="_blank"> 请单击此处查看此图的更大版本. </a>

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作者没有竞争的财务利益透露。

对基因的透彻了解需要达到人类基因组测序的全部潜能, 从而提供新的生物学见解8。目前, 只有通过其数据描述和标题 (即、元数据)1来搜索联机表数据集的方法。这就严重限制了表数据的搜索类型。模式表数据的搜索工具对于探索不同表标记之间的关系至关重要, 这可能导致新的生物学见解。根据数据的内容而不是元数据进行搜索的 GeNemo 是同类的第一个服务, 它将表数据中的模式与已发布的托管库 (如编码数据库) 与用户生成或下载的数据集5进行比较。这标志着表搜索工具的可用性的开始, 这是世界各地的研究人员广泛访问的, 就像基于文本的序列搜索工具在二十世纪九十年代得到广泛应用一样。目前, 除了 GeNemo 以外, 没有其他模式在线搜索工具可供表数据使用。
使用 GeNemo 的一个潜在的例子是搜索 co-appearing 组蛋白修饰和其他表观遗传标记与转录因子 E2F6 在人类胚胎干细胞 (一个例子 E2F6 绑定信号文件是在编码数据门户可用或在https://sysbio.ucsd.edu/public/xcao3/ENCODESample/ENCFF001UBC.bed)。通过使用此文件作为查询对 H1-hESC 中的所有编码数据集进行搜索, GeNemo 将显示 E2F6 绑定信号与 H3K4me1、H3K4me2、H3K4me3 和 H3K27me3 一起大量丰富, 这与现有的研究表明, E2F6 通过H3K27 的甲基化9。另一方面, 似乎有定位的 E2F6 和 CtBP2 绑定网站, 这是已知的互动与一个因素在同一家庭, E2F710。这些结果为整个基因组反对大量的表观遗传标记, 转录因子结合信号, 和其他信号在编码中可以相当容易地获得与 GeNemo, 这可以提供所有潜在的目标, 进一步分析。
由于第一次发布5 GeNemo 作为基于 web 的表数据搜索工具, 因此 GeNemo 的结果部分已更新为与 GeNemo 的前页具有匹配的外观。旧的结果部分紧密地镜像了 UCSC 的基因组浏览器结果部分, 并且很大程度上依赖于远程 UCSC 服务器的显示。随着新的接口, GeNemo 是更 user-friendly, 不再依赖于 UCSC 基因组服务器 (即使数据仍然是获取远程)。这使得 GeNemo 更健壮, 而且由于 UCSC 服务器上的代码更改而不易受到问题的影响。此外, GeNemo 的新的、更快的聚合物界面为用户提供了更多的工具来可视化和分析数据中的模式。
关键步骤包括提供适当的输入文件和选择要搜索的数据磁道。强烈鼓励用户尝试各种跟踪选择功能, 以熟悉选择过程以及如何将不同的命令组合在一起以实现预期的结果。特别要注意的是, "add" 函数需要添加所选的查询曲目, 而 "过滤器" 或 "排除" 可以分别用作逻辑门命令 "and" 和 "or"。在实现搜索之前, 需要使用 "Update" 函数来影响所有选择。当没有返回结果时, 用户可以检查输入数据文件, 搜索更多的曲目或增加搜索范围。每当出现错误时, 都会弹出一个窗口, 定义错误的确切内容。但也有一些含糊不清的错误。例如, 当窗口表示 "没有上传任何文件" 时, 或者没有上传文件, 或者上载的文件不是可接受的格式, 因此程序无法正确读取。文件上传可接受的文件格式包括床和波峰格式文件的两个上传方法, 和要人的在线链接只上传。这些文件格式的 zip 版本也可以接受。
此方法的当前局限性包括尚未优化算法和在 GeNemo 中使用的函数。GeNemo 还不能就任何返回的数据集的解释提供任何指导。这项任务是由用户, 这需要在生物基因组和基因的重要知识和专长。另外, 当前的另一个限制是用户不能更改搜索的灵敏度和噪音级别。我们希望在未来的模式搜索功能和数据集收集方面继续改进和扩展 GeNemo。

最近的技术进步允许快速扩展表或功能基因组数据保存, 这已经超过了相关的分析工具的开发, 以提取生物的洞察力。分析表数据的一个重要方法是搜索用户生成的数据和数据保存, 特别是那些来自 DNA 元素 (编码)1项目的百科全书, 以匹配可能导致新知识的模式。例如, 在基因组中定义的基因座上发现两个不同表标记的相似性, 可能表明不同分子在染色质构象和转录调控上的协调作用2 ,3,4。
传统的基于文本的搜索引擎在这方面是无效的, 因为, 与 DNA 序列不同, 表数据主要存在于强度或功能基因组区域的格式中。GeNemo, 站立为基因尼莫 (在寻找尼莫), 被开发为解决这未满足的需要使用模式搜索5。该算法利用马尔可夫链蒙特卡洛最大化过程5。用户可以从保存处下载自己的数据, 或者从数据库中搜索一组在线表数据, 以确定模式的相似性。
GeNemo 的当前版本有一个更新的显示, 接口更加健壮地与加利福尼亚大学, 圣克鲁斯 (UCSC) 基因组浏览器6, 并且较少易受起因于后者的变动引起的问题。特别是, 虽然 GeNemo 的结果页过去是基于 UCSC 基因组浏览器界面, 当前版本的 GeNemo 支持其自己的结果页面, 因此不再是负面影响的结构变化的 UCSC 基因组浏览器。GeNemo 可以使用任何基因组信号, 包括蛋白质结合, 蛋白修饰, 染色质可及性, 拓扑域等, 作为一个查询, 以寻找 colocalized/类似的片段之间的已知数据集大财团。因此, 研究不同的表数据与大规模基因组项目所产生的已知数据之间的关系是一个重要的工具。

<table border="0" cellpadding="0" cellspacing="0" style="border-collapse:
 collapse;width:515pt" width="687">
	<tbody>
		<tr height="21" style="height:15.75pt">
			<td class="xl66" height="21" style="height:15.75pt;width:162pt" width="216">GENEMO</td>
			<td class="xl67" style="width:139pt" width="185">https://www.genemo.org</td>
			<td class="xl66" style="width:89pt" width="119"></td>
			<td class="xl65" style="width:125pt" width="167">Comparative Epigenome Browser</td>
		</tr>
	</tbody>
</table>

pattern-based search of epigenomic data using genemo

与针对基因组或 RNA 测序数据的健壮的基于文本的搜索工具相比, 目前用于模式搜索表和其他功能基因组数据的方法非常有限。GeNemo 是第一个完成这个目标的在线搜索工具。用户在浏览器可扩展数据 (床)、峰值和要人格式中输入他们的功能基因组数据, 并可以搜索任何三种格式的数据。用户可以指定要搜索的数据集类型, 从各种在线数据集中进行选择, 并使用 DNA 元素 (编码) 的百科全书表示不同的表标记、转录因子绑定站点和染色质hypersensitivities 或性在特定的细胞类型, 发育阶段或物种 (老鼠或人类)。GeNemo 返回与输入数据匹配的基因组区域列表, 可以在浏览器中查看, 也可在床文件格式中下载。升级后的 GeNemo 改进了图形显示, 具有更强大的界面, 并且由于加利福尼亚大学圣克鲁斯 (UCSC) 基因组浏览器的变化, 不再容易出现错误。讨论常见问题的疑难解答步骤。随着功能基因组数据的数量呈指数级增长, 迫切需要开发和完善新的生物工具, 如 GeNemo 用于数据分析和解释。

在图 5中显示的是模拟搜索。选择了人类物种, 并将相应的样本文件用作输入数据文件。此外, 还选择了图 3中所示的默认磁道。共有363个匹配的区域, 第一个区域显示在展示页中。可以看出, 从17036000到17038000的强度模式, 在1号染色体上的输入文件和其中一个选择的轨道是非常相似的。

Watch this Scientific Journal Video about Pattern-based Search of Epigenomic Data Using GeNemo at JoVE.com

Pattern-based Search of Epigenomic Data Using GeNemo

与 DNA 序列数据不同, 表数据并不容易受到基于文本的搜索。这里介绍的程序使用升级版本的 GeNemo, 一个基于网络的生物信息学工具, 进行模式搜索的相似性, 表数据比较可用的在线数据库, 包括百科全书的 DNA 元素与用户的数据。

利用 GeNemo 模式搜索表数据

Compared with the robust text-based search tools for genomic or RNA sequencing data, current methodologies for pattern-based searches of epigenomic and ...

pattern-based-search-of-epigenomic-data-using-genemo

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

5.0K 次观看.  University of California San Diego. 与 DNA 序列数据不同, 表数据并不容易受到基于文本的搜索。这里介绍的程序使用升级版本的 GeNemo, 一个基于网络的生物信息学工具, 进行模式搜索的相似性, 表数据比较可用的在线数据库, 包括百科全书的 DNA 元素与用户的数据。

视频: Pattern-based Search of Epigenomic Data Using GeNemo

Fabrication of Micro-tissues using Modules of Collagen Gel Containing Cells

This protocol describes the fabrication of a type of micro-tissues called modules.  The module approach generates uniform, scalable and vascularized tissues.  The modules can be made of collagen as well as other gelable or crosslinkable materials.  They are approximately 2 mm in length and 0.7 mm in diameter upon fabrication but shrink in size with embedded cells or when the modules are coated with endothelial cells.  The modules individually are small enough that the embedded cells are within the diffusion limit of oxygen and other nutrients but modules can be packed together to form larger tissues that are perfusable.  These tissues are modular in construction because different cell types can be embedded in or coated on the modules before they are packed together to form complex tissues.  There are three main steps to making the modules: (1) neutralizing the collagen and embedding cells in it, (2) gelling the collagen in the tube and cutting the modules and (3) coating the modules with endothelial cells.

Creation of micro-tissues using cylindrical collagen gels, called modules, that contain embedded cells and which surface is coated with endothelial cells.

微组织使用胶原蛋白的模块的制备凝胶含有细胞

This protocol describes the fabrication of a type of micro-tissues called modules.  The module approach generates uniform, scalable and vascularized ...

科研

生物工程

Induction of Adhesion-dependent Signals Using Low-intensity Ultrasound

In multicellular organisms, cell behavior is dictated by interactions with the extracellular matrix. Consequences of matrix-engagement range from regulation of cell migration and proliferation, to secretion and even differentiation. The signals underlying each of these complex processes arise from the molecular interactions of extracellular matrix receptors on the surface of the cell. Integrins are the prototypic receptors and provide a mechanical link between extracellular matrix and the cytoskeleton, as well as initiating some of the adhesion-dependent signaling cascades. However, it is becoming increasingly apparent that additional transmembrane receptors function alongside the integrins to regulate both the integrin itself and signals downstream. The most elegant of these examples is the transmembrane proteoglycan, syndecan-4, which cooperates with &alpha;5&beta;1-integrin during adhesion to fibronectin. In vivo models demonstrate the importance of syndecan-4 signaling, as syndecan-4-knockout mice exhibit healing retardation due to inefficient fibroblast migration1,2. In wild-type animals, migration of fibroblasts toward a wound is triggered by the appearance of fibronectin that leaks from damaged capillaries and is deposited by macrophages in injured tissue. Therefore there is great interest in discovering strategies that enhance fibronectin-dependent signaling and could accelerate repair processes.
The integrin-mediated and syndecan-4-mediated components of fibronectin-dependent signaling can be separated by stimulating cells with recombinant fibronectin fragments. Although integrin engagement is essential for cell adhesion, certain fibronectin-dependent signals are regulated by syndecan-4. Syndecan-4 activates the Rac1 protrusive signal3, causes integrin redistribution1, triggers recruitment of cytoskeletal molecules, such as vinculin, to focal adhesions4, and thereby induces directional migration3. We have looked for alternative strategies for activating such signals and found that low-intensity pulsed ultrasound (LIPUS) can mimic the effects of syndecan-4 engagement5. In this protocol we describe the method by which 30 mW/cm2, 1.5 MHz ultrasound, pulsed at 1 kHz (Fig. 1) can be applied to fibroblasts in culture (Fig. 2) to induce Rac1 activation and focal adhesion formation. Ultrasound stimulation is applied for a maximum of 20 minutes, as this combination of parameters has been found to be most efficacious for acceleration of clinical fracture repair6. The method uses recombinant fibronectin fragments to engage &alpha;5&beta;1-integrin, without engagement of syndecan-4, and requires inhibition of protein synthesis by cycloheximide to block deposition of additional matrix by the fibroblasts., The positive effect of ultrasound on repair mechanisms is well documented7,8, and by understanding the molecular effect of ultrasound in culture we should be able to refine the therapeutic technique to improve clinical outcomes.

This protocol describes the stimulation of cultured fibroblasts with low-intensity pulsed ultrasound, which drives focal adhesion formation and Rac1 activation by mimicking engagement of the transmembrane matrix receptor, syndecan-4. This approach allows investigation of a successful clinical technique at the cellular level, thereby providing opportunities for refinement of the therapy.

诱导粘附依赖使用低强度超声波信号

In multicellular organisms, cell behavior is dictated by interactions with the extracellular matrix. Consequences of matrix-engagement range from ...

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Microtubules are cytoskeletal polymers which play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires microtubules that are stiff and straight enough to span a significant fraction of the cell diameter. As a result, the microtubule persistence length, a measure of stiffness, has been actively studied for the past two decades1. Nonetheless, open questions remain: short microtubules are 10-50 times less stiff than long microtubules2-4, and even long microtubules have measured persistence lengths which vary by an order of magnitude5-9.
	Here, we present a method to measure microtubule persistence length. The method is based on a kinesin-driven microtubule gliding assay10. By combining sparse fluorescent labeling of individual microtubules with single particle tracking of individual fluorophores attached to the microtubule, the gliding trajectories of single microtubules are tracked with nanometer-level precision. The persistence length of the trajectories is the same as the persistence length of the microtubule under the conditions used11. An automated tracking routine is used to create microtubule trajectories from fluorophores attached to individual microtubules, and the persistence length of this trajectory is calculated using routines written in IDL.
	This technique is rapidly implementable, and capable of measuring the persistence length of 100 microtubules in one day of experimentation. The method can be extended to measure persistence length under a variety of conditions, including persistence length as a function of length along microtubules. Moreover, the analysis routines used can be extended to myosin-based acting gliding assays, to measure the persistence length of actin filaments as well.

A method to measure the persistence length or flexural rigidity of biopolymers is described. The method uses a kinesin-driven microtubule gliding assay to experimentally determine the persistence length of individual microtubules and is adaptable to actin-based gliding assays.

使用滑翔分析生物大分子的抗弯刚度测量

Microtubules are cytoskeletal polymers which  play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires ...

Production of Large Numbers of Size-controlled Tumor Spheroids Using Microwell Plates

Tumor spheroids are increasingly recognized as an important in vitro model for the behavior of tumor cells in three dimensions. More physiologically relevant than conventional adherent-sheet cultures, they more accurately recapitulate the complexity and interactions present in real tumors. In order to harness this model to better assess tumor biology, or the efficacy of novel therapeutic agents, it is necessary to be able to generate spheroids reproducibly, in a controlled manner and in significant numbers.
The AggreWell system consists of a high-density array of pyramid-shaped microwells, into which a suspension of single cells is centrifuged. The numbers of cells clustering at the bottom of each microwell, and the number and ratio of distinct cell types involved depend only on the properties of the suspension introduced by the experimenter. Thus, we are able to generate tumor spheroids of arbitrary size and composition without needing to modify the underlying platform technology. The hundreds of microwells per square centimeter of culture surface area in turn ensure that extremely high production levels may be attained via a straightforward, nonlabor-intensive process. We therefore expect that this protocol will be broadly useful to researchers in the tumor spheroid field.

We introduce a protocol for the generation of large numbers (thousands to hundreds of thousands) of uniform size- and composition-controlled tumor spheroids, using commercially available microwell plates.

生产尺寸控制肿瘤细胞球体采用微孔板大数

Tumor spheroids are increasingly recognized as an important in vitro model for the behavior of tumor cells in three dimensions. More physiologically ...

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

The bottleneck for cellular 3D electron microscopy is feature extraction (segmentation) in highly complex 3D density maps. We have developed a set of criteria, which provides guidance regarding which segmentation approach (manual, semi-automated, or automated) is best suited for different data types, thus providing a starting point for effective segmentation.

从体素知识:实用指南复电镜三维数据的分割

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, ...

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals

A methodology is described herein for representing anatomical imaging data within crystals. We create scaled three-dimensional models of biomedical imaging data for use in Sub-Surface Laser Engraving (SSLE) of crystal glass. This tool offers a useful complement to computational display or three-dimensionally printed models used within clinical or educational settings.

缩放生物医学层析成像数据的解剖模型的创建和相关联的标签玻璃晶体的随后的子表面激光雕刻（SSLE）

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data ...

Fragility Assessment of Bovine Cortical Bone Using Scratch Tests

Bone is a complex hierarchical material with five distinct levels of organization. Factors like aging and diseases like osteoporosis increase the fragility of bone, making it fracture-prone. Owing to the large socio-economic impact of bone fracture in our society, there is a need for novel ways to assess the mechanical performance of each hierarchical level of bone. Although stiffness and strength can be probed at all scales &#8211; nano-, micro-, meso-, and macroscopic &#8211; fracture assessment has so far been confined to macroscopic testing. This limitation restricts our understanding of bone fracture and constrains the scope of laboratory and clinical studies. In this research, we investigate the fracture resistance of bone from the microscopic to the mesoscopic length scales using micro scratch tests combined with nonlinear fracture mechanics. The tests are performed in the short longitudinal orientation on bovine cortical bone specimens. A meticulous experimental protocol is developed and a large number (102) of tests are conducted to assess the fracture toughness of cortical bone specimens while accounting for the heterogeneity associated with bone microstructure.

This study assesses the fracture toughness of bovine cortical bone at the sub-meso levels using microscopic scratch tests. This is an original, objective, rigorous, and reproducible method proposed to probe fracture toughness below the macroscopic scale. Potential applications are studying changes in bone fragility due to diseases like osteoporosis.

牛皮质骨脆性评估的划痕试验

Bone is a complex hierarchical material with five distinct levels of organization. Factors like aging and diseases like osteoporosis increase the ...

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Science relies on increasingly complex data sets for progress, but common data management methods such as spreadsheet programs are inadequate for the growing scale and complexity of this information. While database management systems have the potential to rectify these issues, they are not commonly utilized outside of business and informatics fields. Yet, many research labs already generate "medium sized", low velocity, multi-dimensional data that could greatly benefit from implementing similar systems. In this article, we provide a conceptual overview explaining how databases function and the advantages they provide in tissue engineering applications. Structural fibroblast data from individuals with a lamin A/C mutation was used to illustrate examples within a specific experimental context. Examples include visualizing multidimensional data, linking tables in a relational database structure, mapping a semi-automated data pipeline to convert raw data into structured formats, and explaining the underlying syntax of a query. Outcomes from analyzing the data were used to create plots of various arrangements and significance was demonstrated in cell organization in aligned environments between the positive control of Hutchinson-Gilford progeria, a well-known laminopathy, and all other experimental groups. In comparison to spreadsheets, database methods were enormously time efficient, simple to use once set up, allowed for immediate access of original file locations, and increased data rigor. In response to the National Institutes of Health (NIH) emphasis on experimental rigor, it is likely that many scientific fields will eventually adopt databases as common practice due to their strong capability to effectively organize complex data.

Many researchers generate "medium-sized", low-velocity, and multi-dimensional data, which can be managed more efficiently with databases rather than spreadsheets. Here we provide a conceptual overview of databases including visualizing multi-dimensional data, linking tables in relational database structures, mapping semi-automated data pipelines, and using the database to elucidate data meaning.

在组织工程中高效管理中等规模、低速度、多维数据的数据库

Science relies on increasingly complex data sets for progress, but common data management methods such as spreadsheet programs are inadequate for the ...

Simple, Affordable, and Modular Patterning of Cells using DNA

The relative positioning of cells is a key feature of the microenvironment that organizes cell-cell interactions. To study the interactions between cells of the same or different type, micropatterning techniques have proved useful. DNA Programmed Assembly of Cells (DPAC) is a micropatterning technique that targets the adhesion of cells to a substrate or other cells using DNA hybridization. The most basic operations in DPAC begin with decorating cell membranes with lipid-modified oligonucleotides, then flowing them over a substrate that has been patterned with complementary DNA sequences. Cells adhere selectively to the substrate only where they find a complementary DNA sequence. Non-adherent cells are washed away, revealing a pattern of adherent cells. Additional operations include further rounds of cell-substrate or cell-cell adhesion, as well as transferring the patterns formed by DPAC to an embedding hydrogel for long-term culture. Previously, methods for patterning oligonucleotides on surfaces and decorating cells with DNA sequences required specialized equipment and custom DNA synthesis, respectively. We report an updated version of the protocol, utilizing an inexpensive benchtop photolithography setup and commercially available cholesterol modified oligonucleotides (CMOs) deployed using a modular format. CMO-labeled cells adhere with high efficiency to DNA-patterned substrates. This approach can be used to pattern multiple cell types at once with high precision and to create arrays of microtissues embedded within an extracellular matrix. Advantages of this method include its high resolution, ability to embed cells into a three-dimensional microenvironment without disrupting the micropattern, and flexibility in patterning any cell type.

Here we present a protocol to micropattern cells at single-cell resolution using DNA-programmed adhesion. This protocol uses a benchtop photolithography platform to create patterns of DNA oligonucleotides on a glass slide and then labels cell membranes with commercially available complementary oligonucleotides. Hybridization of the oligos results in programmed cell adhesion.

使用DNA对细胞进行简单、经济、模块化的图案化

The relative positioning of cells is a key feature of the microenvironment that organizes cell-cell interactions. To study the interactions between cells ...

Modulating Shape of Polyester Based Polymersomes using Osmotic Pressure

Polymersomes are membrane-bound, bilayer vesicles created from amphiphilic block copolymers that can encapsulate both hydrophobic and hydrophilic payloads for drug delivery applications. Despite their promise, polymersomes are limited in application due to their spherical shape, which is not readily taken up by cells, as demonstrated by solid nanoparticle scientists. This article describes a salt-based method for increasing the aspect ratios of spherical poly(ethylene glycol) (PEG)- based polymersomes. This method can elongate polymersomes and ultimately control their final shape by adding sodium chloride in post-formation dialysis. Salt concentration can be varied, as described in this method, based on the hydrophobicity of the block copolymer being used as the base for the polymersome and the target shape. Elongated nanoparticles have the potential to better target the endothelium in larger diameter blood vessels, like veins, where margination is observed. This protocol can expand therapeutic nanoparticle applications by utilizing elongation techniques in tandem with the dual-loading, long-circulating benefits of polymersomes.

Polymersomes are self-assembled polymeric vesicles that are formed in spherical shapes to minimize Gibb's Free Energy. In the case of drug delivery, more elongated structures are beneficial. This protocol establishes methods to create more rod-like polymersomes, with elongated aspect ratios, using salt to induce osmotic pressure and reduce internal vesicle volumes.

使用渗透压力调节聚酯聚合物的形状

Polymersomes are membrane-bound, bilayer vesicles created from amphiphilic block copolymers that can encapsulate both hydrophobic and hydrophilic payloads ...