Optimized pipeline for personalized neurobiological insights from single patient-derived Neurospheres

This pipeline presents a refined approach for deriving personalized neurobiological insights from iPSC-derived neurospheres. By employing Tandem Mass Tag (TMT) labeling, we optimized sample pooling and multiplexing for robust comparative analysis across experimental conditions, maximizing data yield per sample. Through single-patient-derived neurospheres-composed of neural progenitor cells, early neurons, and radial glia-this study explores proteomic profiling to mirror the cellular complexity of neurodevelopment more accurately than traditional 2D cultures. Given their enhanced relevance, these 3D neurospheres serve as a valuable model for elucidating neurogenesis, differentiation, and neuropathological mechanisms, contributing to the advancement of in vitro neural models and reducing dependency on animal models. SIGNIFICANCE: This study evaluates ten protein extraction protocols using TMT 10-plex labeling to optimize proteomic analysis from single neurospheres. It compares cost, protein yield, and the ability to detect differentially expressed proteins, identifying methods like SPEED and S-Trap as efficient for high-throughput studies, while FASP excels in peptide yield. TMT labeling enhances protein identification, particularly for low-abundance proteins, and allows pre-fractionation to maximize analysis from limited samples. However, challenges such as limited PTM analysis and the potential loss of minor proteins highlight the importance of selecting protocols based on specific research goals. This work contributes to optimizing proteomic workflows for in vitro neural models, advancing single-cell analysis with minimal reliance on animal models.