Title : Transcriptomic profiling of a DRG–3D mOEC Co-Culture platform for prognostic biomarker discovery in spinal cord injury
Abstract:
Background and Aims:Spinal cord injury (SCI) is a severe neurological disorder characterised by permanent sensorimotor dysfunction and substantial long-term disability. Among cell-based therapy treatment in SCI, mucosal olfactory ensheathing cells (mOECs) have been shown a significant role in preclinical studies and is now advancing into world's first human clinical trials. However, an urgent need for a biomarker panel that will help to trace the injury progression before and after treatment. Dorsal root ganglion (DRG) neurons represent a physiologically relevant sensory in vitro model for investigating axonal regeneration and neuron–glia interactions following SCI. This study established a DRG–3D mOEC co-culture platform to facilitate transcriptomic biomarker discovery and identify molecular signatures associated with neuronal regeneration following SCI.
Methods: Primary DRG neurons and mOECs were harvested from postnatal day 7 (P7) DsRed mice and incorporated into a physiologically relevant three-dimensional (3D) co-culture model. Whole-transcriptome sequencing (RNA-seq) was performed to compare transcriptomic profiles across intact, injured, and mOEC-treated DRG neurons. Differential gene expression analysis was performed using DESeq2 and edgeR, applying a significance threshold of false discovery rate (FDR)-adjusted P < 0.05. Differentially expressed genes (DEGs) were prioritised according to statistical significance and biological relevance, followed by Gene Set Enrichment Analysis (GSEA), protein–protein interaction (PPI) and network analysis to identify enriched biological pathways and central regulatory hub genes associated with regenerative responses.
Results: Transcriptomic profiling identified 1,318 significantly DEG that clearly distinguished intact, injured, and mOEC-treated groups. Sequential prioritisation refined these findings to a panel of 50 candidate genes, which was further narrowed to 17 high-confidence regulatory genes demonstrating consistent injury and treatment responsive expression. Functional enrichment analysis revealed that injury induced transcriptional changes were predominantly associated with inflammatory signalling, extracellular matrix remodelling, and cytoskeletal reorganisation, whereas mOEC treatment significantly enriched pathways involved in neuronal survival, axon guidance, and regenerative signalling. Protein interaction network analysis identified central hub genes occupying key regulatory positions within the regenerative network, highlighting promising candidates for prognostic biomarker development and therapeutic response monitoring.
Conclusion: This study establishes a physiologically relevant DRG–mOEC co-culture platform for SCI biomarker discovery. Transcriptomic and network analyses identified candidate differentially expressed genes (DEGs) associated with neuronal regeneration and therapeutic response, providing a foundation for future validation using proteomic analyses of bodily fluids, including serum and cerebrospinal fluid (CSF), in preclinical and clinical studies.
