Cell-Compatible, Multicomponent Protein Arrays with Subcellular Feature Resolution
Cell-Compatible, Multicomponent Protein Arrays with Subcellular Feature Resolution
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DOI：
10.1002/smll.200800363
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发表时间：
2008-10-01
期刊：
影响因子：
13.3
通讯作者：
Anderson, Daniel G.
中科院分区：
文献类型：
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作者：
Mei, Ying;Cannizzaro, Christopher;Anderson, Daniel G.
NIH-PA 作者的手稿表面已显示出对研究和控制各种细胞行为的实用性。[1-7] 特别是，特征尺寸小于单个细胞的蛋白质图案已被证明可用作控制细胞活动的工具。[4, 8] 迄今为止，由于现有打印方法的技术限制，大多数研究仅限于单一蛋白质因子的研究。在此，我们描述了微尺度直写（MDW）技术的开发，用于生成具有多个组件的亚细胞特征尺寸的复杂 ECM 蛋白质阵列。基于原子力显微镜的自动打印技术被开发出来，可以通过编程生成具有多种 ECM 蛋白的细胞相容表面，亚细胞特征尺寸为 6-9 微米。系统地生成了具有不同间距和组成的细胞兼容的双组分 ECM 蛋白质阵列。然后研究这些阵列对模型细胞系（人肌成纤维细胞）的细胞附着和扩散的影响。有趣的是，在亚细胞分辨率下精确调整两个组件的间距和放置可以导致细胞排列的增加。鉴于体内细胞微环境的复杂性，我们相信这里描述的 MDW 方法可以普遍适用于生物材料表面的研究和优化。具有明确化学成分和空间分辨率的蛋白质阵列具有在各种生物医学和生物技术应用中的潜力。[9-11]最近的研究表明，在微尺度分辨率下以明确的 ECM 蛋白质模式控制细胞粘附和扩散的能力可以影响许多细胞行为，包括分裂、迁移、凋亡和分化。[1-7]已经开发了许多创建蛋白质图案的方法，包括喷墨印刷[12, 13]和浸笔纳米光刻（DPN）[14]以及最常见的微接触印刷（μcp）。[15-17]μcp的第一步通常是在PDMS中创建母版或印模。然后使用印模通过与给定基材直接接触来生成蛋白质图案。在直接接触（印刷）过程中，主图案中的所有特征都会一次性转移。然而，要生成具有多个组件的复杂图案，需要额外的印刷步骤，并且这些步骤必须与先前印刷的现有图案正确对齐。从单独的组件中获得高分辨率特征所需的微米级对齐是具有挑战性的，特别是当组件的数量大于两个时。 [18-20] 或者，以串行方式直接将蛋白质写入表面的方法，例如 MDW、喷墨打印和 DPN，允许直接对齐并轻松生成多组件蛋白质阵列。 [21, 22]
NIH-PA Author Manuscript surfaces have shown utility for the study and control of a variety of cellular behaviors.[1–7] In particular, the patterning of proteins with feature sizes smaller than a single cell have demonstrated potential application for use as tools to control cellular activity.[4, 8] To date, most research has been limited to studies with single protein factors due to technical limitations of existing printing methods. Herein, we describe the development of a microscale direct writing (MDW) technology for the generation of complex ECM protein arrays at subcellular feature size with multiple components. Automated printing techniques based on atomic force microscopy were developed to allow programmable generation of cell-compatible surfaces with multiple ECM proteins, at a subcellular feature size of 6–9 microns. Cell-compatible, two component ECM protein arrays were systematically generated with varying spacing and composition. These arrays were then studied for their effects on cellular attachment and spreading of a model cell line, human myofibroblasts. Interestingly, the precise tuning of spacing and placement two components at subcellular resolution can lead to an increase in cellular alignment. Given the complexity of the in vivo cellular microenvironment, we believe the MDW methods described here could prove generally applicable for the study and optimization of biomaterial surfaces.Protein arrays with defined chemical composition and spatial resolution have potential for use in a variety of biomedical and biotechnological applications.[9–11] Recent studies have shown that the ability to control cell adhesion and spreading with well-defined ECM protein patterns at microscale resolution can effect a number of cell behaviors, including division, migration, apoptosis and differentiation.[1–7] A number of methods for creating protein patterns have been developed, including inkjet printing,[12, 13] and Dip-Pen Nanolithography (DPN),[14] and most commonly, microconatct printing (μcp).[15–17] The first step of μcp is generally the creation of a master or stamp in PDMS. The stamp is then used to generate protein patterns by direct contact with a given substrate. During the direct contact (printing) process, all of the features in the master pattern are transferred at one time. However, to generate complex patterns with multiple components, additional printing steps are required, and these must be properly aligned with the existing pattern from the previous printing. The micron-scale alignment necessary to make high resolution features from separate components is challenging, in particular when the number of components is greater than two.[18–20] Alternatively, methods that directly write proteins onto surfaces in the serial manner, such as MDW, inkjet printing and DPN, allow for straightforward alignment and the facile generation of the multiple components protein arrays.[21, 22]