Facilitating neural stem/progenitor cell niche calibration for neural lineage differentiation by polyelectrolyte multilayer films

被引:15
作者
Lee, I-Chi [1 ]
Wu, Yu-Chieh [1 ]
机构
[1] Chang Gung Univ, Grad Inst Biochem & Biomed Engn, Taoyuan 333, Taiwan
关键词
Neural stem/progenitor cells (NSPCs); Polyelectrolyte multilayer (PEM) films; Neural network; Neurite outgrowth; Synapses; GROWTH-FACTOR; STEM-CELLS; IN-VITRO; PROLIFERATION; SUBSTRATE; STIFFNESS; MODULATION; STABILITY; ADHESION; NEURONS;
D O I
10.1016/j.colsurfb.2014.05.033
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Neural stem/progenitor cells (NSPCs) are a possible candidate for advancing development and lineage control in neural engineering. Differentiated protocols have been developed in this field to generate neural progeny and to establish neural networks. However, continued refinement is required to enhance differentiation specificity and prevent the generation of unwanted cell types. In this study, we fabricated a niche-modulated system to investigate surface effects on NSPC differentiation by the formation of polyelectrolyte multilayer (PEM) films governed by electrostatic interactions of poly-L-glutamine acid as a polyanion and poly-L-lysine as a polycation. The serum- and chemical agent-free system provided a clean and clear platform to observe in isolation the interaction between surface niche and stem cell differentiation. We found that NSPCs were inducible on PEM films of up to eight alternating layers. In addition, neurite outgrowth, neuron percentage, and synaptic function were regulated by layer number and the surface charge of the terminal layer. The average process outgrowth length was over 500 mu m on PLL/PLGA((n=7.5)) only after 3 days of culture. Moreover, the quantity and quality of the differentiated neurons were enhanced as the number of layers increased, especially when the terminal layer was poly-L-lysine. Our results achieve important targets of neural engineering, including long processes, large neural network size, and large amounts of functional neurons. Our methodology for nanoscale control of material deposition can be successfully applied for surface modification, neural niche modulation, and neural engineering applications. (C) 2014 Published by Elsevier B.V.
引用
收藏
页码:54 / 65
页数:12
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