A simplified workflow with end-point validation of real-time electrical cell-substrate impedance sensing of retinoic acid stimulated neurogenesis in human SH-SY5Y cells in vitro

Autor: Julia Joos-Vandewalle, Vanessa Steenkamp, Earl Prinsloo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: BMC Research Notes, Vol 16, Iss 1, Pp 1-9 (2023)
Druh dokumentu: article
ISSN: 1756-0500
90059441
DOI: 10.1186/s13104-023-06369-0
Popis: Abstract Objective Retinoic acid (RA) is known to transition proliferating SH-SY5Y neuroblastoma cells towards functional neurons. However, the activity of RA is restricted due to its photolability where any findings from prolonged time course observations using microscopy may alter outcomes. The aim of the study was to establish a real-time, long-term (9-day) protocol for the screening of differentiation events using Electrical cell-substrate impedance sensing (ECIS). Results and discussion A differentiation baseline for SH-SY5Y cells was established. Cells were seeded and exposed to repeated spikes of RA using the xCELLigence real-time cell analyser single plate (RTCA-SP) for real-time monitoring and identification of differentiation activity over a 9 day period in order to be more representative of differentiation over a prolonged timeline. Specific features associated with differentiation (growth inhibition, neurite outgrowths) were confirmed by end-point analysis. RA-induced growth inhibition and assumed phenotypic changes (i.e. neurite outgrowth) were identified by the xCELLigence analysis and further confirmed by end-point metabolic and phenotypic assays. Change in cellular morphology and neurite outgrowth length was identified by end-point fluorescence detection followed by computational analysis. Based on this it was possible to identify SH-SY5Y phenotypic differentiation with distinct phases observed over 9 days using Electric cell-substrate impedance sensing (ECIS) cell index traces providing a path to application in larger scale neurotrophic factor screening using this scalable technology.
Databáze: Directory of Open Access Journals
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