Accurate nanoelectrode recording of human pluripotent stem cell-derived cardiomyocytes for assaying drugs and modeling disease
Year: 2017
Type: article
Abstract: The measurement of the electrophysiology of human pluripotent stem cell-derived cardiomyocytes is critical for their biomedical applications, from disease modeling to drug screening. Yet, a method that enables the high-throughput intracellular electrophysiology measurement of single cardiomyocytes in adherent culture is not available. To address this area, we have fabricated vertical nanopillar electrodes that can record intracellular action potentials from up to 60 single beating cardiomyocytes. Intracellular access is achieved by highly localized electroporation, which allows for low impedance electrical access to the intracellular voltage. Herein, we demonstrate that this method provides the accurate measurement of the shape and duration of intracellular action potentials, validated by patch clamp, and can facilitate cellular drug screening and disease modeling using human pluripotent stem cells. This study validates the use of nanopillar electrodes for myriad further applications of human pluripotent stem cell-derived cardiomyocytes such as cardiomyocyte maturation monitoring and electrophysiology-contractile force correlation.
Source: Microsystems & Nanoengineering
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,790
Awards: G1351713346, G1368535900, CAREER: Nanopillar Electrode Arrays for Highly Sensitive Detection of Neuroelectric Activities, G3377603095, G3506141840, G4095189993, Modeling the role of the genome in chemotherapy induced cardiotoxicity using iPSC, Nanoparticle-mediated delivery of allele-specific siRNAs as a novel therapy for dilated cardiomyopathy, G6671297155, G7265336909, G738160294, Engineering external forces for manipulating cargo transport in live neurons, Modeling the role of the genome in chemotherapy induced cardiotoxicity using iPSC, G8293452648, G9000278326, G9000319851
OpenAlex ID: W2595638044
