Transcriptional profiling of intervertebral disc in a post-traumatic early degeneration organ culture model.

INTRODUCTION: The goal of this study is to characterize transcriptome changes and gene regulation networks in an organ culture system that mimics early post-traumatic intervertebral disc (IVD) degeneration. METHODS: To mimic a traumatic insult, bovine caudal IVDs underwent one strike loading. The control group was cultured under physiological loading. At 24 hours after one strike or physiological loading, RNA was extracted from nucleus pulposus (NP) and annulus fibrosus (AF) tissue. High throughput next generation RNA sequencing was performed to identify differentially expressed genes (DEGs) between the one strike loading group and the control group. Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes analyses were performed to analyze DEGs and pathways. Protein-protein interaction (PPI) network was analyzed with cytoscape software. DEGs were verified using qRT-PCR. Degenerated human IVD tissue was collected for immunofluorescence staining to verify the expression of DEGs in human disc tissue. RESULTS: One strike loading resulted in significant gene expression changes compared with physiological loading. In total 253 DEGs were found in NP tissue and 208 DEGs in AF tissue. Many of the highly dysregulated genes have known functions in disc degeneration and extracellular matrix (ECM) homeostasis. ACTB, ACTG, PFN1, MYL12B in NP tissue and FGF1, SPP1 in AF tissue were verified by qRT-PCR and immunofluorescence imaging. The identified DEGs were involved in focal adhesion, ECM-receptor interaction, PI3K-AKT, and cytokine-cytokine receptor interaction pathways. Three clusters of PPI networks were identified. GO enrichment revealed that these DEGs were mainly involved in inflammatory response, the ECM and growth factor signaling and protein folding biological process. CONCLUSION: Our study revealed different DEGs, pathways, biological process and PPI networks involved in post-traumatic IVD degeneration. These findings will advance the understanding of the pathogenesis of IVD degeneration, and help to identify novel biomarkers for the disease diagnosis.