Single cell RNA sequencing reveals a shift in cell function and maturation of endogenous and infiltrating cell types in response to acute intervertebral disc injury

The intervertebral disc (IVD) is a spinal joint that accumulates damage with age but has limited tissue repair capabilities. IVD damage progresses into degeneration, and IVD degeneration is a leading cause of lower back pain. There are no effective therapies to treat IVD degeneration, but understanding the cell populations that change and respond to injury will uncover targets to restore IVD function. Mesenchymal stem cells (MSCs) are cells within the IVD that can potentially replenish the cells lost after IVD damage. To identify the cell populations of the IVD and how they change with injury, we performed single cell RNA sequencing of IVD tissue 7 days post injury and analyzed the differences in gene regulation. We identified diverse cells populations such as IVD specific tissues, immune cells, vascular cells, and MSCs. We discovered the presence of Saa2 and Grem1 expressing MSCs that become less stem cell-like and express higher levels of IVD gene markers after injury. We also determined that Saa2 and Grem1 have slightly different expression patterns in IVD tissues, and this expression becomes reduced after injury. These MSCs could be used in future stem cell therapies to prevent IVD degeneration. Control IVDs were isolated from female, 12-week old C57BL/6 (#000664) mouse tails in the coccygeal “CC” region CC12/13 through CC16/17. Injured IVDs were conducted using a 30G needle to bilaterally puncture regions CC5/6 through CC9/10. Control and Injured IVDs are from the same animal. Punctures were performed by using digital palpation to identify CC5/6 through CC9/10, puncturing each level with a sterile 30G needle. Control and Injured IVDs from 6 mice were pooled so that there was a total of 30 IVDs per group rendered into a single cell suspension and snap frozen. Snap frozen cells were thawed, and fluorescently activated cell sorting (FACS) was performed to sort out the viable cells from cell debris and dead cells using DAPI and then resuspended in PBS + 0.04% nonacetylated BSA for preparation of scRNASeq using a Chromium Controller (10X Genomics). Library preparation was performed using Chromium Single Cell 30 GEM, Library & Gel Bead Kit v3 (10X Genomics) following the manufacturer’s protocol and sequenced using Illumina NextSeq 500. Alignment of scRNASeq data to the mouse genome (mm10) and gene counting was completed utilizing the 10XGenomics Cell Ranger. Subsequently, output files from the Cell Ranger ‘count’ were read into Seurat v3 for further analysis17. Cells with fewer than 250 detected genes or genes that were expressed by fewer than 5 cells were excluded from the analysis. After normalization of the data and the most variable genes identified, the data were scaled, and the dimensionality of the data was reduced by principal component analysis (PCA). A non-linear dimensional reduction was then performed via uniform manifold approximation and projection (UMAP) and various cell clusters were identified.