我们感谢京都大学 iCeMS 的 Nakatsuji 教授提供人类 ES 细胞。我们还感谢东京理工大学的圆山教授在使用原子力显微镜方面的支持。日本促进科学学会慷慨提供资金 (jsp; 22350104、23681028、25886006和 24656502);新能源和工业技术发展组织 (尼德) 和泰尔茂生命科学基金会也提供了资金。iCeMS 由日本教育、文化、体育、科学和技术部 (下个) 世界总理国际研究中心倡议支持。这项工作的一部分是由京都大学纳米技术中心和 AIST 纳米处理设施的支持, 在 "纳米技术平台项目" 赞助的日本下个。

1. MACME 阵列的制作
注: 所有材料和设备都列在材料表中。
<ol><li>
碳纤维阵列和微流控结构模具的掩模制备
	<ol>
<li>使用3维计算机图形软件包 (表 1) 创建用于微流控结构的碳纤维阵列和模具的三维 (3D) 掩码图像。 注:3D 图像由3D 打印机读取和打印。打印的掩码和模具具有与在步骤1.1.1 中使用图形软件定义的3D 图像相同的尺寸。</li>
		<li>使用3D 打印机在这些设计的基础上打印掩码和模具。 注:在该协议中, 采用了30的 UV 固化树脂喷墨式3D 打印机。打印机分辨率为 635 x 400 dpi 和15µm, 分别为 x、y 和 Z, 但实际 X、y 分辨率约为四倍。</li>
	</ol>
</li>
	<li>
碳纤维阵列准备 (图 3A)
	<ol>
<li>为静电纺丝制备聚合物溶液。<ol>
<li>用四氢呋喃稀释 13% PMGI 液体 9% (瓦特/v)22。</li>
			<li>溶解 0.08 g 的 PS (数字平均分子量 (锰): 13万) 在 THF: 甲基酰胺 (1:1 体积比)21, 并添加 THF: 甲基酰胺, 使体积达到最后1毫升 (8% (w/v) PS 解决方案)。</li>
			<li>在水中溶解0.1 克 GT: 乙酸乙酯 (1:1. 6:2. 1 体积比), 加水: 醋酸: 乙酸乙酯, 使体积达到最终1毫升 (10% (w/v) GT 溶液), 如所述23、31。</li>
		</ol>
</li>
		<li>使用磁控溅射机, 在聚苯乙烯 (PS) 底板 (127.7 x 85.5 毫米) 上沉积一个 5 nm 厚度的薄铂层, 在静电纺丝装置中充当阴极。</li>
		<li>将每个聚合物溶液装入5毫升的注射器中, 配备23克不锈钢钝针。</li>
		<li>将注射器放在注射器泵上, 并将针头固定在12厘米外, 与静电纺丝装置的收集器分开。</li>
		<li>将注射器针连接至高压电源, 并将其设置为11伏。</li>
		<li>设定泵浦率为0.2 毫升/小时。</li>
		<li>保持温度和湿度在30摄氏度和 < 30% (v/v)。</li>
		<li>在台阶1.2.2 上, 把面罩放在底板上。</li>
		<li>通过改变静电纺丝时间 (例如, 20、60、90和 180s), 在底板上通过具有不同密度的掩孔制造纳米纤维。</li>
		<li>从底板上取下面罩。 注意.乙醇可以喷洒在静电纺丝 GT 纳米纤维上, 然后去除面罩, 以避免剥离 GT 纳米纤维与面具。</li>
		<li>重复步骤 1.2. 4-1. 2.10 直到完成碳纤维阵列制造。</li>
		<li>将碳纤维阵列放置在干燥中25摄氏度, 以蒸发剩余溶剂。</li>
		<li>交联 GT 纳米纤维与0.2 米 1-乙基 3-(3-dimethylaminopropyl) carbodiimide 盐酸盐 (EDC) 和 0.2 M n-琥珀 (NHS) 在乙醇在25°c 4 h23。</li>
		<li>用 99.5% (v/v) 乙醇和真空干燥在25摄氏度为16小时冲洗 GT 纳米纤维两次。</li>
	</ol>
</li>
	<li>
微流控结构的制备 (图 3B)
	<ol>
<li>混合2克的聚硅烷固化剂和20克的基 (1:10 重量比;前)。24
</li>
		<li>将预混合材料倒入步骤1.2 中制造的模具上。</li>
		<li>将预聚硅烷混合物干燥为30分钟。</li>
		<li>在65摄氏度的烤箱中, 以16小时的温度固化预混合料。</li>
	</ol>
</li>
	<li>
MACME 阵列的装配 (图 3B)
	<ol>
<li>剥离从模具中固化的1.3.4 结构, 用 70% (v/v) 乙醇清洗。</li>
		<li>在该结构的底部处理大气电晕放电32。 注:在本协议中, 电晕在3层或4次的整个表面上用一个 "方便的" 电晕放电装置排出。用大气电晕放电代替氧等离子体处理, 改变表面粘附。</li>
		<li>快速装配碳纤维阵列的结构。</li>
		<li>烤箱烘烤在 65°C 2 天。</li>
	</ol>
</li>
</ol>2. 将干细胞加载到 MACME 阵列中
<ol><li>对于 H9 人类胚胎干细胞 (干细胞) 的常规培养, 保持细胞在异的化学定义培养基 hPSC 维护33补充10µM Y-27632 岩石抑制剂34 (命名 hPSC 培养基) 在35毫米细胞培养用基底膜凝胶基质 (MG) 涂敷的盘子。</li>
	<li>通过细胞每4到7天使用重组胰蛋白酶样蛋白酶。</li>
	<li>用99.5% 乙醇消毒 MACME 阵列, 将其装入腔内10分钟, 然后取出乙醇。重复此步骤3次。</li>
	<li>引进12µL 毫克, 10 µg/毫升及其与受精 (钒氮), 0.1% (w/v) GT 进入控制培养室, 并孵化的商会在37°c 为 1 h 在房间表面涂上它们。 注:在本协议中, MG、钒氮和 GT 被选作细胞黏附和培养的参考蛋白。由于 MG 和钒氮是用于维持 hPSC 自我更新的标准细胞培养基质, 它们被用作阳性对照;二维 GT 涂层 (2DGT) 或非涂层 (NC) 被用作负控制。</li>
	<li>在 MACME 阵列中引入预热 hPSC 介质。在37摄氏度孵化出30分钟的房间。</li>
	<li>洗 H9 人类胚胎干细胞培养在一个35毫米菜与 DPBS, 添加0.5 毫升的重组胰蛋白酶样蛋白酶的菜肴和孵化37摄氏度1分钟, 并仔细吸入只有上清液混合蛋白酶。 注:在吸入步骤, 细胞没有分离。</li>
	<li>立即加入 hPSC 培养基, 轻轻地将培养基放在盘子表面上, 反复将细胞分离, 转移到15毫升的锥形管上。</li>
	<li>离心机在 200 x g 的3分钟内吸出上清, 并在预热的 hPSC 培养基中悬浮细胞。</li>
	<li>将细胞悬浮液12µL (1.2 x 106细胞/毫升) 引入每个微流控腔。 注:使用微将细胞从另一个腔室引入。由于被播种到腔室的细胞数量与室底的柱密度成正比, 即使使用相同细胞悬浮的样品, 初始细胞播种密度也可以控制。确保吹打的完成。加载后, 用棉尖棒从腔内取出多余的介质。MACME 阵列与常用的实验室吸管和自动吸管系统兼容, 不需要任何特殊设备。</li>
	<li>每12小时改变 hPSC 培养基, 培养4天。 注:介质 (1.6、3.2 和6.4 µL) 的恒定体积通过使用不同大小的分庭来维持。在静态条件下培养细胞, 以最小化剪切应力, 除了细胞培养培养基的交换35,36。</li>
</ol>3. 定量单细胞分析
<ol><li>
板上荧光细胞染色 注:为了分析自我更新 hPSCs 的表型变化, 本协议选择了该协议的三个关键型式标记: OCT4、5-乙炔 2 '-脱氧尿苷 (教育局) 和蛋白 V, 以测定干细胞、增殖和凋亡的状态。分别 (图 2b)。4 ', 6-diamidino-2-苯基吲哚 (DAPI) 用于识别细胞核。OCT4 是干细胞的关键转录因子之一。<ol>
<li>在 hPSC 培养基 MACME 阵列中孵化 H9 干细胞, 辅以10µM, 37 °c 30 分钟。</li>
		<li>洗后与蛋白结合缓冲 (10 毫米 HEPES (pH 7.4), 140 毫米氯化钠, 2.5 毫米 CaCl2), 染色的细胞与橙色荧光染料-蛋白 V 共轭在20°c 15 分钟。</li>
		<li>固定在 pbs 的细胞与 4% (v/v) 多聚甲醛在20°c 15 分钟, 然后冲洗细胞与 PBS 两次。</li>
		<li>Permeabilize 细胞使用 PBS 与 0.3% (v/v) 海卫 X-100 在20°c 16 小时。 注:多聚甲醛削弱了塑料基板和一个微流控流体结构之间的粘结。因此, 在步骤3.2.1 的阵列上, 也可以在这一步之后执行。</li>
		<li>用红色荧光染料叠氮化物在三基反应缓冲器中孵育细胞, 在20摄氏度时为30分钟。</li>
		<li>孵化细胞在阻塞缓冲 (PBS 与 5% (v/v) 正常山羊血清, 5% (v/v) 正常驴血清, 3% (w/v) 牛血清白蛋白, 0.1% (v/v) Tween-20, 和 0.1% (瓦特/v) n-月桂-β-maltoside) 在4摄氏度为 16 h。</li>
		<li>孵育在 PBS 与 0.5% (v/v) 海卫 X-100 溶液和人 OCT3/4 抗体 (鼠 IgG) 在4°c 为 16 h。</li>
		<li>用绿色荧光染料标记驴抗鼠 IgG (H + L) 在37°c 培养60分钟。</li>
		<li>孵育在 PBS 与 DAPI 在20°c 30 分钟。</li>
		<li>用 pbs 替换 pbs DAPI。</li>
		<li>保持 MACME 阵列在4°c, 直到图像采集。</li>
	</ol>
</li>
	<li>
图像采集 (图 4)
	<ol>
<li>剥离 MACME 阵列中的微流体结构。</li>
		<li>从 MACME 阵列中取出残余 PBS, 将 pbs 中的 90% (v/v) 甘油应用于细胞, 并将盖玻片在染色细胞上。</li>
		<li>将板块倒置在倒置荧光显微镜的舞台上。</li>
		<li>使用由显微镜成像软件控制的所有机动组件 (舞台、过滤器、快门和焦点系统) 自动获取12位彩色图像。 注意.在这个协议中, 曝光时间被调整到接近最大强度值 (最高像素强度: 4096), 但没有饱和度, 对于每个图像, DAPI, OCT4, 蛋白 V 和教育局。</li>
	</ol>
</li>
	<li>
计算机引导图像处理与荧光信号量化 (图 5) 注意:下面的单元格图像分析是根据前面描述的方法37进行的。<ol>
<li>将彩色图像转换为灰度。</li>
		<li>计算每个 DAPI 图像的单个阈值, 并使用 "大津" 方法, 并将在阈值之上的像素分类为背景和前景。确保前景值对应于 DAPI 的荧光强度。 注:图像分析过程包含5步骤;识别 DAPI 图像中的主要对象, 分别识别 OCT4、蛋白 V 和教育局图像中的次要对象, 以及测量物体的强度。图 3提供了图形用户界面 (GUI) 在图像处理设置上的图像。</li>
		<li>测量每张图像上 OCT4 和教育局的荧光强度。</li>
		<li>用传播方法确定染蛋白 V 的区域, 并量化荧光强度。</li>
	</ol>
</li>
	<li>
3.4. 单细胞成像中单个细胞表型可视化的统计分析
	<ol>
<li>通过居中和缩放这些变量, 使每个表型标记的输入荧光强度正常化, 从而赋予它们同等的权重。</li>
		<li>使用用于统计计算和图形的软件环境执行自组织映射 (SOM) 分析, 如以前的研究38、39所述。<ol>
<li>创建25个 SOM 节点, 其中有四个 "码本" 向量, 对应于四个标记、DAPI、蛋白 V 和 OCT4 的荧光强度。</li>
			<li>将每个微环境中的单个细胞分配到一个 "获胜的" (最相似的) 节点, 并绘制为单元格频率, 根据该值, 获胜节点的本书向量使用加权平均更新, 其中权重为学习率 (在这里, 0.05 作为默认值)。 注:从包含少于1000个单元格的分庭中省略数据, 因为包含几个单元格的数据集没有提供统计上相关的 SOM 结果。</li>
		</ol>
</li>
		<li>利用聚类软件40中基于皮尔逊关联的平均联动方法, 对 SOM 节点值进行无监督层次聚类。</li>
		<li>将群集数据呈现到树和热图视图41中。</li>
	</ol>
</li>
</ol>

该协议的第一个筛选方法, 建立一个健全的文化系统, 以维护合格的 hPSCs。首先, 我们描述了如何使用与碳纤维阵列 (MACME 阵列) 集成的微流控设备来准备一个具有不同人工 ECMs 和细胞播种密度的平台。第二, 以定量图像为基础的单细胞分型进行50 , 以评估个别细胞结局和行为改变的独特的生物化学和生物物理特征。在该协议中, 在高初始细胞播种密度条件下, 由 GT 碳纤维和正控 ECM 蛋白组成的环境具有未分化状态的特征;快速增殖45和稳定的 OCT4 表达51。这种观察表明, 与 "细胞细胞外基质" 和 "细胞细胞" 相互作用有关的分子机制会影响 hPSCs 的干细胞。
这个策略可以根据用户的目的进行定制。例如, 通过重新设计微流控结构的形状和模式, 可以为各种实验设置调整单元格操作和吞吐量。作为提高吞吐量的另一条途径, 每个房间的入口和出口位置按照96孔板的微板块标准设计, 由生物分子科学协会标准化;因此, 自动机器人液体分配器可用于高通量筛选。为了进一步研究 "细胞 ECM 相互作用" 的分子机制, 通过化学修饰纳米纤维与信号分子 52, 可以使人工细胞微环境更精确地模拟体内条件..
迄今为止, 为筛查细胞微环境而开发的大多数平台都旨在筛选可溶性因子 (例如生长因子和化合物)42、43、44, 但不碳纤维 ECMs, 因为结合不同的制造技术的困难。例如, 碳纤维板在微流控结构和底板之间产生一个小的间隙, 导致它们不稳定的粘合, 从而导致不同样品之间的交叉污染, 因为培养基与另一室的混合物通过小差距。我们的新方法促进了在特定地点的碳纤维矩阵的简单和精确的制造, 并允许它们与底板直接连接, 从而防止不稳定的粘结和交叉污染。此外, 很少有53个与微流体和碳纤维矩阵集成的平台能够被系统地操纵化学和物理线索, 以调查它们对细胞功能的影响, 因为需要的技术整合非常复杂。我们与 MACME 阵列的单细胞分析可以使用一个容易达到的仪器和简单的技术, 并具有很大的潜力, 用于建模细胞环境的发展和细胞生物学研究和药物发现/筛选。

人类多潜能干细胞 (hPSCs)1,2自我更新无限和分化为各种组织血统, 这可能会革命性的药物开发, 细胞治疗, 组织工程和再生医学3,4,5,6. 然而, 一般文化菜肴和微量滴定板的设计并不是为了在细胞层面上精确的物理和化学细胞操作, 而纳米到微表的范围是细胞扩张的关键因素,自我更新和分化。为了解决这个缺点, 研究已经研究了细胞微环境在调节细胞命运决定和细胞功能方面的作用4。近年来, 越来越多的研究已经进行了重建细胞微环境的体外7,8。纳米和微加工工艺通过化学9、10、11、12、13的操作建立了这些微环境, 14、15、16、17和物理18、19、20环境提示。到目前为止, 还没有报告系统地调查在单个平台内对细胞命运决定和功能的化学和物理环境线索的基本机制。
在这里, 我们引入了一个基于简单设计原则的策略来建立一个健壮的筛选平台 (图 1)。首先, 我们描述了使用碳纤维阵列和微流控结构创建多功能、人工细胞微环境的集成平台的开发过程: 多路人工细胞微环境 (MACME) 阵列(图 1A和2A)。碳纤维阵列在碳纤维材料和密度的不同组合中有12种不同的微环境。静电纺丝是用来制造纳米纤维的。碳纤维材料, 如聚苯乙烯 (PS)21, polymethylglutarimide (PMGI)22, 和明胶 (GT)23, 旨在测试其化学性质, 这可能影响细胞黏附和维护干细胞 (图 2B)。碳纤维密度随静电纺丝时间的改变而变化, 生成的纳米纤维根据其密度 (DNF, D = XLow/低/中/高) 来定义。微流控结构由烷48细胞培养室组成, 可沿96井微板块的标准尺寸定位。是一种生物相容和气体可交换聚合物, 通常用于制造微流控器件24。每个微流控通道设计为700µm 宽和8.4 毫米长, 其边缘有两个入口 (表 1)。分庭有不同的高度 (250, 500 和1000µm) 来操纵初始细胞播种密度 (0.3, 0.6, 1.2 x 10 细胞/厘米 5), 这可能与生存, 增殖和分化的 hPSCs2(图 2C)。进入腔室的细胞数量与室底板上的柱密度成正比, 从而控制了初始细胞播种密度, 并将同一细胞悬浮液引入不同高度的培养室。所有通道的设计是≥ 250-µm-高26 , 以尽量减少低氧张力27和剪切应力28对细胞的影响。通道高度为250、500和1000µm, 这里缩写为 XCD, 分别为 X = 低、中、高。不同碳纤维密度和初始细胞播种密度的环境被缩短为 "Material_NF density_Cell 密度" (如 GT_HighNF_HighCD: 一种以高密度 GT 纳米纤维和高初始细胞播种为特征的环境;密度)。
随后, 我们描述了如何进行单细胞分析, 系统地调查细胞的行为, 以应对环境因素 (图 1B)。作为概念证明, 我们确定了 hPSC 自我更新的最佳细胞环境, 这是 hPSC 维护的关键功能 (图 1B)29。基于图像的细胞术, 其次是统计分析, 允许对细胞环境的个体细胞表型反应进行定量解释。在多种细胞功能中, 本文提供了一个详细的程序来确定保持 hPSC 自我更新的最佳条件。

<table><tbody><tr><td>Polystyrene (PS)</td><td>Sigma</td><td>#182435</td><td>Average Mw: 290,000, average Mn: 130,000</td></tr><tr><td>Polymethylglutarimide (PMGI)</td><td>MicroChem</td><td>G113113</td><td></td></tr><tr><td>Gelatin (GT)</td><td>Sigma</td><td>G2625</td><td>From porcine skin, type A</td></tr><tr><td>Sylgard 184 silicone elastomer kit</td><td>Doe Corning Toray</td><td>#1064291</td><td>PDMS curing agent and silicone elastomer base are components of this kit.</td></tr><tr><td>OpenSCAD</td><td></td><td></td><td>This is a free 3D computer graphics software (http://www.openscad.org/) used for designing the mold of the microfluidic device.</td></tr><tr><td>AutoCAD 2014</td><td>Autodesk</td><td></td><td>This is a 3D computer graphics software (https://www.autodesk.com/products/autocad/overview) used for design of the mask used on nanofiber-array preparation.</td></tr><tr><td>3D printer, AGILISTA-3000</td><td>Keyence</td><td></td><td></td></tr><tr><td>UV-curable resin, AR-M2</td><td>Keyence</td><td></td><td>This is used for 3D printing by Agilista.</td></tr><tr><td>Acetic acid</td><td>Sigma</td><td>#338826</td><td>&amp;ge;99.99%</td></tr><tr><td>Ethyl acetate</td><td>Sigma</td><td>#270989</td><td>Anhydrous, 99.8%</td></tr><tr><td>Tetrahydrofuran (THF)</td><td>Sigma</td><td>#401757</td><td></td></tr><tr><td>MSP-30T</td><td>Vacuum Device</td><td></td><td>Magnetron sputtering machine</td></tr><tr><td>Nunc OmniTray</td><td>Thermo Fisher Scientific</td><td>#242811</td><td>This is a polystyrene baseplate on which the nanofiber array is created. This plate size is typically 127.7 x 85.5 mm.&amp;nbsp;</td></tr><tr><td>Gun-type corona discharge machine</td><td>Shinko Electric &amp;amp; Instrumentation</td><td>CFG-500</td><td>This handy device is used to generate corona for activation of the bottom surface of the PDMS layer at step 1.5 &quot;Assembly of the MACME arrays&quot; in the protocol.</td></tr><tr><td>5 mL syringe</td><td>Terumo</td><td>SS-05SZ</td><td></td></tr><tr><td>Stainless-steel blunt needle (23-gauge)</td><td>Nipro</td><td>#2166</td><td>Outside diameter and length are 0.6 and 32 mm, respectively.</td></tr><tr><td>High-voltage power supply</td><td>TechDempaz</td><td></td><td></td></tr><tr><td>1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide, hydrochloride</td><td>Dojindo</td><td>W001</td><td></td></tr><tr><td>N-Hydroxysuccinimide</td><td>Sigma</td><td>#56480</td><td></td></tr><tr><td>Matrigel hESC-Qualified Matrix</td><td>Corning</td><td>#354277</td><td>This protein is refered as basement membrane gel matrix in the protocol.</td></tr><tr><td>CellAdhere Vitronectin, Human, Solution</td><td>STEMCELL Technologies</td><td>#07004</td><td></td></tr><tr><td>TeSR-E8</td><td>STEMCELL Technologies</td><td>#05940</td><td>Feeder-free, xeno-free culture medium for maintenance of human ES and iPS cells</td></tr><tr><td>Y-27632</td><td>Wako Pure Chemical Industries</td><td>#253-00513</td><td></td></tr><tr><td>TrypLE Express Enzyme (1X), phenol red</td><td>Thermo Fisher Scientific</td><td>#12605028</td><td>This ia a recombinant trypsin-like protease for dissociation of adherant mammalian cells.</td></tr><tr><td>Click-iT EdU Imaging Kit with Alexa Fluor 647 Azides</td><td>Thermo Fisher Scientific</td><td>C10086</td><td>The fluorescent labeling of proliferating cells in on-plate fluorescent staining was performed along the product manual of this kit.</td></tr><tr><td>Annexin V, Alexa Fluor 594 conjugate</td><td>Thermo Fisher Scientific</td><td>A13203</td><td></td></tr><tr><td>4&#039;,6-diamidino-2-phenylindole (DAPI)</td><td>Thermo Fisher Scientific</td><td>D1306</td><td></td></tr><tr><td>Oct-3/4 Antibody (C-10)</td><td>Santa Cruz Biotechnology</td><td>sc-5279</td><td></td></tr><tr><td>Donkey Anti-Mouse IgG H&amp;amp;L (DyLight 488)</td><td>abcam</td><td>ab96875</td><td>This is a secondary antibody used in on-plate fluorescent cell staining.</td></tr><tr><td>ECLIPSE Ti-E</td><td>Nikon</td><td></td><td>This is an inverted fluorescence microscope equipped with a CFI Plan Fluor 4&amp;times;/0.13 N.A. objective lens (Nikon), CCD camera (ORCA-R2, Hamamatsu), mercury lamp (Intensilight, Nikon), XYZ automated stage (Ti-S-ER motorized stage with encoders, Nikon), and filter cubes for four fluorescence channels (DAPI, GFP HYQ, TRITC, Cy5; Nikon)</td></tr><tr><td>NIS-Elements Advanced Research</td><td>Nikon</td><td></td><td>This is a microscope imaging software used for automatic image acquisition.</td></tr><tr><td>CellProfiler, Version 2.1.0</td><td></td><td></td><td>This is a free open software for cell image analysis (http://cellprofiler.org/).</td></tr><tr><td>R</td><td></td><td></td><td>SOM analysis is performed by kohonen package of this software. This is freely available (https://www.r-project.org/).</td></tr><tr><td>Cluster 3.0</td><td></td><td></td><td>This is the open source clustering software (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm). Unsupervised hierarchical clustering is performed with this software.</td></tr><tr><td>Java TreeView</td><td></td><td></td><td>This open source software (http://jtreeview.sourceforge.net/) is used to visualize clustering data as a heatmap and a dendrogram.</td></tr><tr><td>H9 human embryonic stem cell</td><td>WiCell Stem Cell Bank</td><td>WA09</td><td></td></tr></tbody></table>

fabrication of a multiplexed artificial cellular microenvironment array

细胞微环境由多种线索组成, 如生长因子、细胞外基质和细胞间相互作用。这些线索是精心编排的, 是调节细胞功能在一个生活系统中的关键。虽然许多研究人员试图研究环境因素与所期望的细胞功能之间的相关性, 但仍有许多未知之处在。这主要是由于缺乏一个适当的方法来模仿这种环境线索的体外, 并同时测试不同的环境提示细胞。在这里, 我们报告一个综合平台的微流控通道和碳纤维阵列, 其次是高含量单细胞分析, 以检查干细胞表型改变的不同环境因素。为了证明该平台的应用, 本研究重点研究了自我更新的人多潜能干细胞 (hPSCs) 的表型。在这里, 我们提出了一个碳纤维阵列的准备程序和微流控结构制造的多复用人工细胞微环境 (MACME) 阵列。此外, 还介绍了单细胞分析、多荧光标记细胞染色、多荧光成像和统计分析的总体步骤。

MACME 阵列: 设计和制造:结合碳纤维技术, 我们利用微流控细胞培养和筛选技术, 以前使用的确定最佳条件 hPSC 自我更新或分化35,36 (图 1)。这非常适合于建立强健的高通量细胞检测方法, 因为细胞培养室和条件是精确可控和可扩展的42,43,44。在这里, 碳纤维阵列是由一个简单的碳纤维沉积方法, 静电纺丝与 3 d-打印掩模。微流控部分是用3维印刷模制作的, 通过多次试验和误差, 方便地设计了硐室结构。MACME 阵列是结合两个部分和包含48环境, 提供不同的生物物理和生物化学的线索, 通过不同的组合碳纤维 ECMs (3 种碳纤维材料和4不同密度或4控制基质蛋白) 和细胞间的相互作用 (初始细胞播种密度的3范围), 如图 2所示。
碳纤维性质和细胞密度对人类胚胎干细胞表型影响的综合评价:在 MACME 阵列上的细胞培养和板上荧光染色 (图 6a) 中, 对所采集的图像进行单细胞测量。为了比较每个数据集中的四表型标记的同质性和非一致性, 该协议使用 SOM 分析38,39, 将高维多参数数据集转换为低维2D 地图。值得注意的是, 由于大多数细胞没有粘附, 所以从这一分析中省略了 PS 纳米纤维和2DGT 矩阵的结果。此外, 排除在这种分析是那些低 CD 的实验, 细胞没有足够的直接 (例如, juxtacrine) 或间接 (分泌) 相互作用, 以生存。在 som 分析之后, 对所有分析样本的 som 节点执行无监督的分层聚类 (图 6B)。通过考虑簇树的高度, 表型差异使我们可以将样本分类为三组: 第一组, 大多数样品龛位包括 GT 纳米纤维、MG_HighCD 和 VN_HighCD;第二组, 含有 GT 纳米纤维 (GT_XLow 和 MidNF_MidCD)、MG_MidCD 或 VN_MidCD 的样品;第三组, 所有 PMGI_NF 样品。
为了研究各组之间的差异, 我们检查了每个组的一个代表性样本 (图 6C;i 组-GT_MidNF_HighCD, 第二组-GT_MidNF_MidCD, 第三组-PMGI_MidNF_HighCD)。在 OCT4 信号方面, 所有组的表达均高于 MG (MG_MidCD)。i 组的特点是高的信号, 表明大多数细胞正在积极增殖。因此, I 组微环境的特点是适合 hPSC 维护的条件, 因为未分化的 hPSCs 通常在细胞周期间隙相缩短45,46时迅速增殖。
GT_MidNF_HighCD 和 GT_MidNF_MidCD 的区别在于它们的初始细胞加载密度。高初始细胞密度增加了细胞与相邻细胞相互作用的机会, 从而增强了它们的生存和增殖47。在初始密度不足 (3.0 x 104细胞/厘米2) 播种的细胞在实验期间 (4 天) 既不存活也不生长。因此, 我们没有把这些样本纳入 SOM 分析;细胞数低于1000年活细胞/室的切断。2DGT 支架上的细胞也被归类为 ii. 类细胞;这些条件不支持 hPSC 自我更新48。GT_MidNF_MidCD 细胞的培养信号丢失, 蛋白 V 水平略有增加, 表明细胞失去了 stemness, 并逐渐成为凋亡。PMGI_MidNF_HighCD, 代表微环境包括 PMGI 碳纤维矩阵, 显示了 OCT4 和其他条件比较大的变化。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57377/57377fig1.jpg"> 图 1.筛选策略, 以确定最佳的细胞微环境调节细胞功能.(A) 多复用人工细胞微环境 (MACME) 阵列的组成部分概述。该阵列由两个主要部分组成: 在基底基底上 (碳纤维阵列) 上图案的碳纤维床和基于烷的微流控结构。MACME 阵列能够准备碳纤维 ECMs 的各种特征 (如碳纤维材料和密度) 和各种细胞播种密度。MACME 阵列的微流体结构具有三微流控通道高度 (250、500和1000µm), 以调节初始细胞播种密度。(B) 利用基于图像的单细胞检测方法, 通过自组织图 (SOM) 的统计数据分析和分层聚类, 定量评价细胞微环境对细胞表型的影响。这个数字是从参考49改编的, 得到威利的许可。<a href="/files/ftp_upload/57377/57377fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57377/57377fig2.jpg"> 图 2.MACME 阵列的设计.(a) 整个 MACME 阵列的头顶和高角度镜头以及碳纤维矩阵 (粉红色) 上的微流控通道 (浅蓝色) 的概念图。每个通道由一个700µm 宽 8.4 mm 长的培养室和两个导入介质和细胞的入口组成。(B) 细胞大小和碳纤维矩阵的比较。细胞高度和碳纤维床范围从1-3 µm 和 0.05-5 0 µm 分别。(C) 每个微流控通道的横断面, 其高度为 250/500/1000 µm。细胞和碳纤维床分别代表蓝色圆圈和橙色线。每个腔室的宽度和长度相同, 但高度 (250、500和1000µm), 每个腔体体积分别为1.6、3.2 和6.4 µL。图 2C中的黑色虚线矩形表示图 2B。图 2从参考49被适应了从威利的允许。<a href="/files/ftp_upload/57377/57377fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57377/57377fig3.jpg"> 图 3.MACME 阵列的制作.(a) 制作碳纤维阵列。在底板上, 用一组带花纹孔的掩模, 对基板上的多个碳纤维矩阵进行模化。铂涂层是为了便于在塑料底板上碳纤维沉积。用3D 打印机制备了具有不同孔型的掩模。在镀铂涂层区域的掩蔽下, 将板罩套放在采集屏上, 进行了正常的静电纺丝。最初的纳米纤维是通过面罩上的孔在板上的铂涂层位置形成的。额外的碳纤维床是通过更换现有的面具和重复的程序在板上捏造的。(B) 制作微流控结构。采用 UV 固化树脂的3D 打印机打印的模具, 形成微流控装置的聚甲基丙烯酸酯层。在铸造后, MACME 阵列通过附加一个基于的微流控层与表面活化的碳纤维阵列进行组装。图 3从参考49被适应了从威利的允许。<a href="/files/ftp_upload/57377/57377fig3large.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/57377/57377fig4.jpg"> 图 4.图形用户界面 (GUI) 图像, 用于显微图像采集.<a href="/files/ftp_upload/57377/57377fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57377/57377fig5.jpg"> 图 5.图形用户界面 (GUI) 图像, 用于单单元分型的计算机引导图像处理.图像分析过程包含5步骤;(A) 识别 DAPI 图像中的主要物体, (B D) 分别识别 OCT4、蛋白 V 和教育局图像中的次要物体, 并测量物体的强度。<a href="/files/ftp_upload/57377/57377fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57377/57377fig6.jpg"> 图 6.微环境因子改变 H9 干细胞表型的分型和分类。(A) 在高初始播种密度下培养的 H9 干细胞在明胶 (GT) 纳米纤维 (GT_HighNF_HighCD) 上的免疫荧光图像, 染色三种细胞表型标记 (OCT4、干细胞;细胞增殖;蛋白 V、凋亡) 和 DAPI 细胞细胞核。(B) 无监督的分层聚类的热图和 dendrograms。根据表型的相似性, 将经测试的微环境分为三组, 具有明显的特征。组 i 包括 GT 纳米纤维, MG_HighCD 和 VN_HighCD。第二组由 GT 纳米纤维 (GT_XLow 和 MidNF_MidCD)、MG_MidCD 或 VN_MidCD 的样品组成。所有 PMGI_NF 样本都聚集到第三组。在热图中, 粉红色和蓝色分别表示 SOM 计数地块中的高和低的细胞频率。(C) 从每个组的一个代表性样本中分配1000年细胞的量化标记表达水平 (第一组 GT_MidNF_HighCD、第二组 GT_MidNF_MidCD 和第三组 PMGI_MidNF_HighCD)。第二十五和第七十五百分点被表明作为箱子极限。胡须延伸到四分位范围的1.5 倍, 从第二十五和第七十五百分点。每组实验重复三次。图 6C从参考49被适应了与威利的允许。<a href="/files/ftp_upload/57377/57377fig6large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<table fo:keep-together.within-page="1"><tbody>
<tr>
<td>名字</td>
			<td>通道长度 (毫米)</td>
			<td>通道宽度 (微米)</td>
			<td>通道高度 (微米)</td>
			<td>进口/出口直径 (微米)</td>
			<td>进口/出口高度 (微米)</td>
			<td>模具长度 (mm)</td>
			<td>模具宽度 (mm)</td>
			<td>模具高度 (mm)</td>
		</tr>
<tr>
<td>模具</td>
			<td>8。4</td>
			<td>700</td>
			<td>250/500/1000</td>
			<td>800</td>
			<td>3000</td>
			<td>127.76</td>
			<td>85.48</td>
			<td>14.35</td>
		</tr>
<tr>
<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
<tr>
<td>名字</td>
			<td>厚度 (微米)</td>
			<td>孔长 (mm)</td>
			<td>孔宽 (mm)</td>
			<td>掩码长度 (mm)</td>
			<td>掩码宽度 (mm)</td>
			<td>模具高度 (mm)</td>
			<td>行偏移量 (mm)</td>
			<td>列偏移量 (mm)</td>
		</tr>
<tr>
<td>面具</td>
			<td>1000</td>
			<td>6</td>
			<td>5</td>
			<td>123。5</td>
			<td>80。2</td>
			<td>14.35</td>
			<td>11.24</td>
			<td>14.38</td>
		</tr>
</tbody></table>表1。微流控结构的模具尺寸和碳纤维模式的掩模。

Watch this Scientific Journal Video about Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array at JoVE.com

Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

多路人工细胞微环境阵列的制备

本文介绍了用于制备多路人工细胞微环境 (MACME) 阵列的详细方法, 用于对模拟体内细胞微环境的物理和化学线索进行高通量操作, 并用单细胞分析方法确定人类多潜能干细胞 (hPSCs) 的最佳细胞环境。

Cellular microenvironments consist of a variety of cues, such as growth factors, extracellular matrices, and intercellular interactions. These cues are ...

fabrication-multiplexed-artificial-cellular-microenvironment

Universidad San Sebastian

Research

JoVE Journal

Bioengineering

8.4K 次观看.  Kyoto University. 本文介绍了用于制备多路人工细胞微环境 (MACME) 阵列的详细方法, 用于对模拟体内细胞微环境的物理和化学线索进行高通量操作, 并用单细胞分析方法确定人类多潜能干细胞 (hPSCs) 的最佳细胞环境。

视频: Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

微机械动态细胞培养平台

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

科研

生物工程

High-throughput Protein Expression Generator Using a Microfluidic Platform

Rapidly increasing fields, such as systems biology, require the development and implementation of new technologies, enabling high-throughput and high-fidelity measurements of large systems. Microfluidics promises to fulfill many of these requirements, such as performing high-throughput screening experiments on-chip, encompassing biochemical, biophysical, and cell-based assays1. Since the early days of microfluidics devices, this field has drastically evolved, leading to the development of microfluidic large-scale integration2,3. This technology allows for the integration of thousands of micromechanical valves on a single device with a postage-sized footprint (Figure 1). We have developed a high-throughput microfluidic platform for generating in vitro expression of protein arrays (Figure 2) named PING (Protein Interaction Network Generator). These arrays can serve as a template for many experiments such as protein-protein 4, protein-RNA5 or protein-DNA6 interactions.
The device consist of thousands of reaction chambers, which are individually programmed using a microarrayer. Aligning of these printed microarrays to microfluidics devices programs each chamber with a single spot eliminating potential contamination or cross-reactivity Moreover, generating microarrays using standard microarray spotting techniques is also very modular, allowing for the arraying of proteins7, DNA8, small molecules, and even colloidal suspensions. The potential impact of microfluidics on biological sciences is significant. A number of microfluidics based assays have already provided novel insights into the structure and function of biological systems, and the field of microfluidics will continue to impact biology.

We present a microfluidic approach for the expression of protein arrays. The device consists of thousands of reaction chambers controlled by micro-mechanical valves. The microfluidic device is mated to a microarray-printed gene library. These genes are then transcribed and translated on-chip, resulting in a protein array ready for experimental use.

利用微流控平台的高通量蛋白质表达发生器

Rapidly increasing fields, such as systems biology, require the development and implementation of new technologies, enabling high-throughput and ...

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications.

This protocol outlines the fabrication of a large-scale, multiplexed two-dimensional DNA or antibody array, with potential applications in cell signaling studies and biomarker detection.

高密度条码抗体芯片的水流模式的指导下制作

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this ...

化学

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly controlled, high-throughput engineered system for measuring the impact of arrayed biochemical signals on cell differentiation. Recent efforts using cell microarrays have demonstrated their utility for combinatorial studies in which many microenvironmental factors are presented in parallel. However, these efforts have focused primarily on investigating the effects of biochemical cues on cell responses. Here, we present a cell microarray platform with tunable material properties for evaluating both cell differentiation by immunofluorescence and biomechanical cell&#8211;substrate interactions by traction force microscopy. To do so, we have developed two different formats utilizing polyacrylamide hydrogels of varying Young&#39;s modulus fabricated on either microscope slides or glass-bottom Petri dishes. We provide best practices and troubleshooting for the fabrication of microarrays on these hydrogel substrates, the subsequent cell culture on microarrays, and the acquisition of data. This platform is well-suited for use in investigations of biological processes for which both biochemical (e.g., extracellular matrix composition) and biophysical (e.g., substrate stiffness) cues may play significant, intersecting roles.

Cell differentiation is regulated by a host of microenvironmental factors, including both matrix composition and substrate material properties. We describe here a technique utilizing cell microarrays in conjunction with traction force microscopy to evaluate both cell differentiation and biomechanical cell&#8211;substrate interactions as a function of microenvironmental context.

细胞分化和牵引力的相关分析高通量细胞芯片平台

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly ...

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial distribution and activities of community members. We have developed a microwell array platform that can be used to rapidly assemble and track thousands of bacterial communities in parallel. This protocol highlights the utility of the platform and describes its use for optically monitoring the development of simple, two-member communities within an ensemble of arrays within the platform. This demonstration uses two mutants of Pseudomonas aeruginosa, part of a series of mutants developed to study Type VI secretion pathogenicity. Chromosomal inserts of either mCherry or GFP genes facilitate the constitutive expression of fluorescent proteins with distinct emission wavelengths that can be used to monitor community member abundance and location within each microwell. This protocol describes a detailed method for assembling mixtures of bacteria into the wells of the array and using time-lapse fluorescence imaging and quantitative image analysis to measure the relative growth of each member population over time. The seeding and assembly of the microwell platform, the imaging procedures necessary for the quantitative analysis of microbial communities within the array, and the methods that can be used to reveal interactions between microbial species area all discussed.

The development of microbial communities depends on a combination of factors, including environmental architecture, member abundance, traits, and interactions. This protocol describes a synthetic, microfabricated environment for the simultaneous tracking of thousands of communities contained in femtoliter wells, where key factors such as niche size and confinement can be approximated.

微孔阵列平台中微生物群落发展的组装与跟踪

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial ...

Snap Chip for Cross-reactivity-free and Spotter-free Multiplexed Sandwich Immunoassays

Multiplexed protein analysis has shown superior diagnostic sensitivity and accuracy compared to single proteins. Antibody microarrays allow for thousands of micro-scale immunoassays performed simultaneously on a single chip. Sandwich assay format improves assay specificity by detecting each target with two antibodies, but suffers from cross-reactivity between reagents thus limiting their multiplexing capabilities. Antibody colocalization microarray (ACM) has been developed for cross-reactivity-free multiplexed protein detection, but requires an expensive spotter on-site for microarray fabrication during assays. In this work, we demonstrate a snap chip technology that transfers reagent from microarray-to-microarray by simply snapping two chips together, thus no spotter is needed during the sample incubation and subsequent application of detection antibodies (dAbs) upon storage of pre-spotted slides, dissociating the slide preparation from assay execution. Both single and double transfer methods are presented to achieve accurate alignment between the two microarrays and the slide fabrication for both methods are described. Results show that &#60;40 &#956;m alignment has been achieved with double transfer, reaching an array density of 625 spots/cm2. A 50-plexed immunoassay has been conducted to demonstrate the usability of the snap chip in multiplexed protein analysis. Limits of detection of 35 proteins are in the range of pg/mL.

We demonstrate a snap chip technology for performing cross-reactivity-free multiplexed sandwich immunoassays by simply snapping two slides. A snap apparatus is used for reliably transferring reagents from microarray-to-microarray. The snap chip can be used for any biochemical reactions requiring colocalization of different reagents without cross-contamination.

无交叉反应和无免疫多路复用夹芯芯片

Multiplexed protein analysis has shown superior diagnostic sensitivity and accuracy compared to single proteins. Antibody microarrays allow for thousands ...

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device

Mimicking in vivo environmental conditions is crucial for in vitro studies on complex life machinery. However, current techniques targeting live cells and organs are either highly expensive, like robotics, or lack nanoliter volume and millisecond time accuracy in liquid manipulation. We herein present the design and fabrication of a microfluidic system, which consists of 1,500 culture units, an array of enhanced peristaltic pumps and an on-site mixing modulus. To demonstrate the capacities of the microfluidic device, neural stem cell (NSC) spheres are maintained in the proposed system. We observed that when the NSC sphere is exposed to CXCL in day 1 and EGF in day 2, the round-shaped conformation is well maintained. Variation in the input order of 6 drugs causes morphological changes to the NSC sphere and the expression level representative marker for NSC stemness (i.e., Hes5 and Dcx). These results indicate that dynamic and complex environmental conditions have great effects on NSC differentiation and self-renewal, and the proposed microfluidic device is a suitable platform for high throughput studies on the complex life machinery.

We present a microfluidic system for high throughput studies on complex life machinery, which consists of 1500 culture units, an array of enhanced peristaltic pumps and an on-site mixing modulus. The microfluidic chip allows for the analysis of the highly complex and dynamic micro-environmental conditions in vivo.

使用高通量微流体设备生成动态环境条件

Mimicking in vivo environmental conditions is crucial for in vitro studies on complex life machinery. However, current techniques targeting live cells and ...

Fabrication and Use of MicroEnvironment microArrays (MEArrays)

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, distinct microenvironments can impose differentiation, migration, and proliferation phenotypes, and on the tissue level the microenvironment processes as complex as morphogenesis and tumorigenesis1. Not only do the cell and molecular contents of microenvironments impact the cells within, but so do the elasticity2 and geometry3 of the tissue. Defined as the sum total of cell-cell, -ECM, and -soluble factor interactions, in addition to physical characteristics, the microenvironment is complex. The phenotypes of cells within a tissue are partially due to their genomic content and partially due to the combinatorial interactions with the microenviroment. A major challenge is to link specific combinations of microenvironmental components with distinctive behaviours.
Here, we present the microenvironment microarray (MEArray) platform for cell-based functional screening of interactions with combinatorial microenvironments4. The method allows for simultaneous control of the molecular composition and the elastic modulus, and combines the use of widely available microarray and micropatterning technologies. MEArray screens require as few as 10,000 cells per array, which facilitates functional studies of rare cell types such as adult progenitor cells. A limitation of the technology is that entire tissue microenvironments cannot be completely recapitulated on MEArrays. However, comparison of responses in the same cell type to numerous related microenvironments, for instance pairwise combinations of ECM proteins that characterize a given tissue, will provide insights into how microenvironmental components elicit tissue-specific functional phenotypes.
MEArrays can be printed using a wide variety of recombinant growth factors, cytokines, and purified ECM proteins, and combinations thereof. The platform is limited only by the availability of specific reagents. MEArrays are amenable to time-lapsed analysis, but most often are used for end point analyses of cellular functions that are measureable with fluorescent probes. For instance, DNA synthesis, apoptosis, acquisition of differentiated states, or production of specific gene products are commonly measured. Briefly, the basic flow of an MEArray experiment is to prepare slides coated with printing substrata and to prepare the master plate of proteins that are to be printed. Then the arrays are printed with a microarray robot, cells are allowed to attach, grow in culture, and then are chemically fixed upon reaching the experimental endpoint. Fluorescent or colorimetric assays, imaged with traditional microscopes or microarray scanners, are used to reveal relevant molecular and cellular phenotypes (Figure 1).

Fabrication and Use of MicroEnvironment microArrays MEArrays

A combinatorial functional screening method for gaining insights into the impacts of the molecular composition of microenvironments on cellular functions is described. The method takes advantage of existing microarray-based technologies to generate arrays of defined combinatorial microenvironments that support cell adhesion and functional analysis.

制造和使用微环境芯片（MEArrays）

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, ...

生物学

Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes and therapeutic responses. Accounting for matrix effects earlier in the drug development pipeline is expected to increase the likelihood of clinical success of novel therapeutics. Biomaterial-based strategies recapitulating specific tissue microenvironments in 3D cell culture exist but integrating these with the 2D culture methods primarily used for drug screening has been challenging. Thus, the protocol presented here details the development of methods for 3D culture within miniaturized biomaterial matrices in a multi-well plate format to facilitate integration with existing drug screening pipelines and conventional assays for cell viability. Since the matrix features critical for preserving clinically relevant phenotypes in cultured cells are expected to be highly tissue- and disease-specific, combinatorial screening of matrix parameters will be necessary to identify appropriate conditions for specific applications. The methods described here use a miniaturized culture format to assess cancer cell responses to orthogonal variation of matrix mechanics and ligand presentation. Specifically, this study demonstrates the use of this platform to investigate the effects of matrix parameters on the responses of patient-derived glioblastoma (GBM) cells to chemotherapy.

The present protocol describes an experimental platform to assess the effects of mechanical and biochemical cues on chemotherapeutic responses of patient-derived glioblastoma cells in 3D matrix-mimetic cultures using a custom-made UV illumination device facilitating high-throughput photocrosslinking of hydrogels with tunable mechanical features.

水凝胶阵列可提高 3D 肿瘤模型中基质成分和治疗药物筛选效果的通量

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes ...

Generation of Multicue Cellular Microenvironments by UV-Photopatterning of Three-Dimensional Cell Culture Substrates

The extracellular matrix is an important regulator of cell function. Environmental cues existing in the cellular microenvironment, such as ligand distribution and tissue geometry, have been increasingly shown to play critical roles in governing cell phenotype and behavior. However, these environmental cues and their effects on cells are often studied separately using in vitro platforms that isolate individual cues, a strategy that heavily oversimplifies the complex in vivo situation of multiple cues. Engineering approaches can be particularly useful to bridge this gap, by developing experimental setups that capture the complexity of the in vivo microenvironment, yet retain the degree of precision and manipulability of in vitro systems.
This study highlights an approach combining ultraviolet (UV)-based protein patterning and lithography-based substrate microfabrication, which together enable high-throughput investigation into cell behaviors in multicue environments. By means of maskless UV-photopatterning, it is possible to create complex, adhesive protein distributions on three-dimensional (3D) cell culture substrates on chips that contain a variety of well-defined geometrical cues. The proposed technique can be employed for culture substrates made from different polymeric materials and combined with adhesive patterned areas of a broad range of proteins. With this approach, single cells, as well as monolayers, can be subjected to combinations of geometrical cues and contact guidance cues presented by the patterned substrates. Systematic research using combinations of chip materials, protein patterns, and cell types can thus provide fundamental insights into cellular responses to multicue environments.

Traditionally, cell culture is performed on planar substrates that poorly mimic the natural environment of cells in vivo. Here we describe a method to produce cell culture substrates with physiologically relevant curved geometries and micropatterned extracellular proteins, allowing systematic investigations into cellular sensing of these extracellular cues.