High Throughput Optimization of Stem Cell Microenvironments

Fan      Yang; Ying      Mei; Robert      Langer; Daniel   G.   Anderson

Abstract

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.

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