A Framework for NGN1-Induced Sensory Neuron Differentiation for Disease Modelling and Drug Screening

Abstract

Background Neuropathic pain is a burdensome, difficult-to-treat, and highly heterogeneous condition with limited therapeutic options, underscoring the need for robust and reproducible human disease models. Human induced pluripotent stem cell (iPSC)–derived sensory neurons provide a promising platform for patient-specific disease modelling and drug screening; however, their translational use is hampered by variability in differentiation efficiency, cellular composition, and functional maturation across protocols and cell lines. Methods Here, we present a standardized and potentially scalable framework for NGN1-driven differentiation of human iPSCs into sensory neurons. Building on a previously published two-step protocol (1), we systematically deconstructed and optimized each stage of differentiation across a large panel of genetically diverse iPSC lines. Results We identified robust parameters for neural crest-like cell (NCLC) generation, established a flow-cytometry–based quality-control strategy for NCLCs, and defined optimal combinations of seeding density and lentiviral multiplicity of infection to maximize sensory-neuron progenitor yield. To improve culture homogeneity, we compared antimitotic selection strategies and demonstrated that tightly timed Ara-C treatment combined with low progenitor seeding density yields consistently pure sensory neuron cultures. We further evaluated maturation under physiologically relevant glucose conditions and performed a systematic review of media compositions to derive two defined maturation media. Morphological, immunocytochemical, transcriptomic, and electrophysiological analyses revealed that time in culture is a major determinant of maturation, while specific supplements such as prostaglandin E₂ (PGE₂) selectively enhance transcriptional signatures associated with nociceptor identity without substantially altering global network activity. Bulk RNA sequencing demonstrated broad expression of sensory neuron and pain-related markers and gene programs across conditions, with long-term maturation and PGE₂ treatment showing the highest similarity to human dorsal root ganglion reference data. Functional assessment using multi-electrode arrays enabled the detection of donor-specific electrophysiological phenotypes, including reproducible hyperexcitability in small-fiber neuropathy patient-derived lines. Conclusions This study establishes a modular, reproducible NGN1-based differentiation workflow with integrated quality checkpoints that accommodates iPSC line-to-line variability. The framework provides a practical foundation for translational sensory-neuron research, patient-specific disease modelling, and scalable drug screening applications.