In today's neurodevelopment and -disease research, human neural stem/progenitor cell-derived networks represent the sole accessible in vitro model possessing a primary phenotype. However, cultivation and moreover, differentiation as well as maturation of human neural stem/progenitor cells are very complex and time-consuming processes. Therefore, techniques for the sensitive non-invasive, real-time monitoring of neuronal differentiation and maturation are highly demanded. Using impedance spectroscopy, the differentiation of several human neural stem/progenitor cell lines was analyzed in detail. After development of an optimum microelectrode array for reliable and sensitive long-term monitoring, distinct cell-dependent impedimetric parameters that could specifically be associated with the progress and quality of neuronal differentiation were identified. Cellular impedance changes correlated well with the temporal regulation of biomolecular progenitor versus mature neural marker expression as well as cellular structure changes accompanying neuronal differentiation. More strikingly, the capability of the impedimetric differentiation monitoring system for the use as a screening tool was demonstrated by applying compounds that are known to promote neuronal differentiation such as the γ-secretase inhibitor DAPT. The non-invasive impedance spectroscopy-based measurement system can be used for sensitive and quantitative monitoring of neuronal differentiation processes. Therefore, this technique could be a very useful tool for quality control of neuronal differentiation and moreover, for neurogenic compound identification and industrial high-content screening demands in the field of safety assessment as well as drug development.
Due to the lack of appropriate cell models as well as automated electrophysiology monitoring technologies, the standardized identification of neurotoxic or protective effects in vitro remains a major problem in today's pharmaceutical ingredient development. Over the past few years, in vivo-like human pluripotent stem cell-derived neuronal networks have turned out to be a promising physiological cell source, if the establishment of robust and time-saving functional maturation strategies based on stable and expandable neural progenitor populations can be achieved. Here, we describe a multi-microelectrode array (MMEA)-based bioelectronics platform that was optimized for long-term electrophysiological activity monitoring of neuronal networks via field potential measurements. Differentiation of small molecule-based neuronal progenitors on MMEAs led to functional neurons within 15 days. More strikingly, these functional neuronal cultures could remain electrophysiologically stable on the MMEAs for more than four weeks. The observed electrophysiological properties correlated with the expression of typical neuron subtype markers and were further validated by specific neurotransmitter applications. With our established monitoring platform, we could show for the first time the long-term stability of the neural stem cell-like progenitor population to differentiate to electrophysiologically active dopaminergic neuronal networks for more than 80 passages. In conclusion, we provide a comprehensive long-term stable field potential monitoring platform based on stem cell-derived human neuronal networks that can be automated and up-scaled for standardized high-content screening applications e.g. in the field of neurotoxic and neuroprotective therapeutics identification.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.