Optimal Production of 3D Neuronal Lineage Population by Morphological Classification.

Background: The increasing prevalence of neurodegenerative diseases and toxic substance exposure highlights the need for neuronal cell models that closely mimic human neurons in vivo. Compared to traditional models, human pluripotent stem cell (hPSC)-derived three-dimensional models mimic human physiological characteristics and complex nervous system interactions. These models enable patient-specific treatments and improve the predictive accuracy of drug toxicity evaluations. However, differentiation efficiency varies based on organoid size, structure, and cell line characteristics, necessitating standardized protocols for consistent outcome.

Methods: The morphological characteristics of hPSC-derived embryonic bodies (EBs) formed by concave microwells were analyzed at the early stage of neuronal differentiation. Criteria were established to identify cells with high differentiation efficiency, enabling the optimization of differentiation methods applicable across various cell lines. Neuronal organoids were generated using a microfluidic-concave chip, and their suitability for drug toxicity testing was assessed.

Results: EBs, formed in 500 µm concave microwells, exhibited the highest efficiency for neuronal cell differentiation. Cavity-like EBs were more suitable for neuronal differentiation and maturation than cystic-like forms. The optimal neuronal lineage differentiation method was established, and the drug toxicity sensitivity of organoids generated from this method was validated.

Conclusions: This study identified EB structures suitable for neuronal lineage differentiation based on morphological classification. Furthermore, this study suggested an optimal method for generating neuronal organoids. This method can be applied to various cell lines, enabling its precise use in patient-specific treatments and drug toxicity tests.