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Issue 7, 2018
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Nanotopography regulates motor neuron differentiation of human pluripotent stem cells

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Abstract

The regulation of human pluripotent stem cell (hPSC) behaviors has been mainly studied through exploration of biochemical factors. However, the current directed differentiation protocols for hPSCs that completely rely on biochemical factors remain suboptimal. It has recently become evident that coexisting biophysical signals in the stem cell microenvironment, including nanotopographic cues, can provide potent regulatory signals to mediate adult stem cell behaviors, including self-renewal and differentiation. Herein, we utilized a recently developed, large-scale nanofabrication technique based on reactive-ion etching (RIE) to generate random nanoscale structures on glass surfaces with high precision and reproducibility. We report here that hPSCs are sensitive to nanotopographic cues and such nanotopographic sensitivity can be leveraged for improving directed neuronal differentiation of hPSCs. We demonstrate early neuroepithelial conversion and motor neuron (MN) progenitor differentiation of hPSCs can be promoted using nanoengineered topographic substrates. We further explore how hPSCs sense the substrate nanotopography and relay this biophysical signal through a regulatory signaling network involving cell adhesion, the actomyosin cytoskeleton, and Hippo/YAP signaling to mediate the neuroepithelial induction of hPSCs. Our study provides an efficient method for large-scale production of MNs from hPSCs, useful for regenerative medicine and cell-based therapies.

Graphical abstract: Nanotopography regulates motor neuron differentiation of human pluripotent stem cells

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Publication details

The article was received on 24 Jul 2017, accepted on 13 Jan 2018 and first published on 16 Jan 2018


Article type: Paper
DOI: 10.1039/C7NR05430K
Nanoscale, 2018,10, 3556-3565

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    Nanotopography regulates motor neuron differentiation of human pluripotent stem cells

    W. Chen, S. Han, W. Qian, S. Weng, H. Yang, Y. Sun, L. G. Villa-Diaz, P. H. Krebsbach and J. Fu, Nanoscale, 2018, 10, 3556
    DOI: 10.1039/C7NR05430K

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