(256ae) Nanotopography Promotes Neuronal Differentiation of Human Induced Pluripotent Stem Cells

Liqing Song¹, Kai Wang², Yong Yang², Yan Li¹

1. Department of Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL 32310, United States

2. Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, WV 26506, United States

Abstract

Inefficient neural differentiation of human pluripotent stem cells (hPSCs), including human induced pluripotent stem cells (hiPSCs), motivates the investigations of the influence of biophysical microenvironment, in particular nanotopography, on hPSC fate decisions recently. However, the contributions of the shape and dimensions of nanotopography to neural lineage commitment of hPSCs have not been well understood. The objective of this study is to delineate the effects of the shape, feature size and height of nanotopography on neuronal differentiation of hiPSCs. Equally spaced, anisotropic nanogratings (500 and 1000 nm in linewidth) and hexagonally arranged isotropic nanopillars (500 nm in diameter, 450 nm in edge-to-edge distance), each having a height of 150 or 560 nm, were seeded with human iPSK3 cells and induced for neuronal differentiation. The gratings of 560 nm height reduced cell proliferation, promoted cytoplasmic localization of Yes-associated protein (YAP), and enhanced neuronal differentiation (up to 60% βIII-tubulin+ cells) compared with the flat control. Differential gene expression of TBR1, a cortical glutamatergic neuron marker, was observed for different substrates, while HOXB4, a marker for hindbrain/spinal cord, was less affected by different nanotopographies. The derived neuronal cells express MAP-2, Tau, Islet-1 (motor neuron progenitors), GABA and vGAT (GABAergic neurons), and glutamate (glutamatergic neurons), indicating the existence of multiple neuronal subtypes. The nanotopography also affected the gene expression of matrix metalloproteinases. This study provides the insights of how different nanotopography parameters (shape, feature size and height) modulate hPSC neural lineage commitment for applications in neurological disease modeling and drug discovery.