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High Throughput Optimization of Stem Cell Microenvironments

机译：高通量优化干细胞微环境

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Stem cells have great potential as cell sources for regenerative medicine due to both their self-renewal and multi-lineage differentiation capacity. Despite advances in the field of stem cell biology, major challenges remain before stem cells can be widely used for therapeutic purposes. One challenge is to develop reproducible methods to control stem cell growth and differentiation. The niche in which stem cells reside is a complex, multi-factorial environment. In contrast to using cells alone, biomaterials can provide initial structural support, and allow cells to adhere, proliferate and differentiate in a three-dimensional environment. Researchers have incorporated signals into the biomaterials that can promote desired cell functions in a spatially and temporally controlled manner. Despite progress in biomaterial design and methods to modulate cellular behavior, many of the complex signal networks that regulate cell-material interactions remain unclear. Due to the vast numbers of material properties to be explored and the complexity of cell-surface interactions, it is often difficult to optimize stem cell microenvironments using conventional, iterative approaches. To address these challenges, high throughput screening of combinatorial libraries has emerged as a novel approach to achieve rapid screening with reduced materials and costs. In this review, we discuss recent research in the area of high throughput approaches for characterization and optimization of cellular interactions with their microenvironments. In contrast to conventional approaches, screening combinatorial libraries can result in the discovery of unexpected material solutions to these complex problems.
机译：干细胞具有自我更新和多系分化的能力，具有作为再生医学细胞源的巨大潜力。尽管干细胞生物学领域取得了进步，但在干细胞被广泛用于治疗目的之前，仍然存在重大挑战。一项挑战是开发可再现的方法来控制干细胞的生长和分化。干细胞所处的环境是一个复杂的，多因素的环境。与单独使用细胞相比，生物材料可以提供初始的结构支持，并允许细胞在三维环境中粘附，增殖和分化。研究人员已将信号整合到生物材料中，这些信号可以以时空受控的方式促进所需的细胞功能。尽管在生物材料设计和调节细胞行为的方法方面取得了进展，但许多调控细胞与材料相互作用的复杂信号网络仍不清楚。由于有待探索的大量材料特性以及细胞表面相互作用的复杂性，通常很难使用常规的迭代方法来优化干细胞微环境。为了解决这些挑战，组合库的高通量筛选已经成为一种新颖的方法，可以以减少的材料和成本实现快速筛选。在这篇综述中，我们讨论了高通量方法领域的最新研究，这些方法用于表征和优化细胞与其微环境的相互作用。与传统方法相反，筛选组合库可导致发现针对这些复杂问题的意料之外的物质解决方案。

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