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NanoMEA: a tool for high-throughput, electrophysiological phenotyping of patterned excitable cells.

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Matrix nanotopographical cues are known to regulate the structure and function of somatic cells derived from human pluripotent stem cell (hPSC) sources. High-throughput electrophysiological analysis of excitable cells derived from… Click to show full abstract

Matrix nanotopographical cues are known to regulate the structure and function of somatic cells derived from human pluripotent stem cell (hPSC) sources. High-throughput electrophysiological analysis of excitable cells derived from hPSCs is possible via multielectrode arrays (MEAs), but conventional MEA platforms use flat substrates and do not reproduce physiologically-relevant tissue-specific architecture. To address this issue, we developed a high-throughput nanotopographically-patterned multielectrode array (nanoMEA) by integrating conductive, ion-permeable, nanotopographic patterns with 48-well MEA plates, and investigated the effect of substrate-mediated cytoskeletal organization on hPSC-derived cardiomyocyte and neuronal function at scale. Using our nanoMEA platform, we found patterned hPSC-derived cardiac monolayers exhibit both enhanced structural organization and greater sensitivity to treatment with calcium blocking or conduction inhibiting compounds when subjected to high-throughput dose-response studies. Similarly, hPSC-derived neurons grown on nanoMEA substrates exhibit faster migration and neurite outgrowth speeds, greater co-localization of pre- and post-synaptic markers, and enhanced cell-cell communication, only revealed through examination of data sets derived from multiple technical replicates. The presented data highlight the nanoMEA as a new tool to facilitate high-throughput, electrophysiological analysis of ordered cardiac and neuronal monolayers, which can have important implications for preclinical analysis of excitable cell function.

Keywords: excitable cells; throughput; throughput electrophysiological; tool; cell; high throughput

Journal Title: Nano letters
Year Published: 2019

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