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A modular cell culture device for generating arrays of gradients using stacked microfluidic flows

机译:模块化细胞培养装置用于利用堆叠的微流体流产生梯度阵列

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摘要

Microfluidics has become increasingly important for the study of biochemical cues because it enables exquisite spatiotemporal control of the microenvironment. Well-characterized, stable, and reproducible generation of biochemical gradients is critical for understanding the complex behaviors involved in many biological phenomena. Although many microfluidic devices have been developed which achieve these criteria, the ongoing challenge for these platforms is to provide a suitably benign and physiologically relevant environment for cell culture in a user-friendly format. To achieve this paradigm, microfluidic designs must consider the full scope of cell culture from substrate preparation, cell seeding, and long-term maintenance to properly observe gradient sensing behavior. In addition, designs must address the challenges associated with altered culture conditions and shear forces in flow-based devices. With this consideration, we have designed and characterized a microfluidic device based on the principle of stacked flows to achieve highly stable gradients of diffusible molecules over large areas with extremely low shear forces. The device utilizes a benign vacuum sealing strategy for reversible application to pre-established cell cultures. We apply this device to an existing culture of breast cancer cells to demonstrate the negligible effect of its shear flow on migratory behavior. Lastly, we extend the stacked-flow design to demonstrate its scalable architecture with a prototype device for generating an array of combinatorial gradients.
机译:微流体技术对于生化线索的研究变得越来越重要,因为它可以对微环境进行精确的时空控制。表征良好,稳定且可重现的生化梯度生成对于理解许多生物学现象涉及的复杂行为至关重要。尽管已经开发了许多达到这些标准的微流体装置,但是这些平台所面临的挑战是以用户友好的形式为细胞培养提供合适的良性和生理相关的环境。为了实现这种范例,微流控设计必须考虑从底物制备,细胞接种和长期维护到细胞培养的整个范围,以正确观察梯度传感行为。此外,设计必须解决与基于流量的设备中培养条件和剪切力变化相关的挑战。考虑到这一点,我们基于堆积流的原理设计并表征了一种微流体装置,以大面积以极低的剪切力实现可扩散分子的高度稳定梯度。该设备利用良性真空密封策略可逆地应用于预先建立的细胞培养物。我们将此设备应用于现有的乳腺癌细胞培养,以证明其剪切流对迁移行为的影响可忽略不计。最后,我们扩展了堆叠流设计,以使用原型设备生成组合梯度数组的方式来展示其可扩展架构。

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