Changes in nucleus pulposus cell atlas and the role of SPP1 during intervertebral disc degeneration: Single-cell sequencing analysis

Changes in nucleus pulposus cell atlas and the role of SPP1 during intervertebral disc degeneration: Single-cell sequencing analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Changes in nucleus pulposus cell atlas and the role of SPP1 during intervertebral disc degeneration: Single-cell sequencing analysis xianzhao wei, Chen Liu, Kun Jiao, Xiaoyu Li, Zixiang Deng, Yajun Cheng, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4737330/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The nucleus pulposus (NP) plays a central role in the pathogenesis of intervertebral disc degeneration (IVDD); however, its internal cellular heterogeneity and molecular mechanisms have not yet been elucidated. Methods ScRNA-seq was used to evaluate the structure of the NP at different degenerative stages in the same individual with IVDD. Unsupervised clustering of cells based on gene expression profiles was performed using the Seurat package and passed to Umap for cluster visualization. A rat disc degeneration model and an in vitro human NP cell degeneration model were established to validate the scRNA-Seq identification results. Results Six NP sub-clusters and immune cells were identified, and their distribution and functional differences between healthy and degenerative states were investigated. Immune cells were present only in degenerated NPs and may trigger NP degeneration. Cellular communication within the NP was altered by the intervention of immune cells. secreted phosphorylated protein 1 (SPP1), secreted by immune cells, plays a major role and is a key molecule in NP degeneration. The results of in vivo animal experiments and in vitro cellular experiments showed that the expression of SPP1 was increased in degenerating NPs. High expression of SPP1 promoted NP degeneration, whereas inhibition of its expression attenuated degeneration. Conclusions Cytoarchitectural changes in NP were revealed by scRNA-Seq. SPP1 is involved in the pathogenesis of disc degeneration and may be a new target for intervention in IVDD. Biological sciences/Computational biology and bioinformatics/Data mining Biological sciences/Molecular biology/DNA damage and repair/Nucleotide excision repair scRNA-Seq IVDD nucleus pulposus SPP1. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Low back pain (LBP) is a leading disabling health condition in humans, with a lifetime prevalence reaching up to 84% 1 Intervertebral disc degeneration (IVDD) is a widely recognized contributor to low back pain 2 . The current treatment of IVDD, mainly including bed rest, rehabilitation, medication, interventional therapy, and surgery 3 , provides only symptomatic relief but fails to reestablish homeostasis of the intervertebral discs (IVDs). An increased understanding of human IVD physiology and pathology is necessary. Mature IVDs consist of a central nucleus pulposus (NP), surrounding annulus fibrosus (AF), and cartilage endplate (CEP), which adjoins the vertebra 4 . The origin of the IVD is heterologous; the NP is believed to be derived from the notochord, and the AF and CEP from the sclerotome 5 . The NP is rich in collagen type II (COL2) and proteoglycans. They facilitate osmotic properties and allow the retention of the fluid required to maintain the NP height and turgor against compressive loads 6 . Thus, it has been widely studied in IVDD. Current studies on the pathophysiology of NP are supported by transcriptomic and epigenomic analyses. However, the development and application of single-cell sequencing technology can help explore the nature of the disease, reveal changes in NP cell types and intercellular communication during degeneration, and provide new ideas for the treatment of disc degeneration. In this study, we profiled 7633 cells from the NP of the same individual at different stages of degeneration. By analyzing single-cell sequencing data, we explored the cellular heterogeneity within the NP before and after degeneration and found that infiltration of immune cells into the interior of the NP affects intercellular crosstalk, with an important role played by the secreted phosphorylated protein 1 (SPP1) signaling pathway. Our results provide new cellular-level insights into the transcriptional alterations associated with IVDD, which could be used in the development of preventative and regenerative strategies for IVDD. Materials and methods Single-cell RNA-seq data analysis Single-cell RNA-seq data processing Unbiased transcriptome-wide scRNA-seq and computational analyses were performed, and raw sequencing data for each sample were converted to matrices of expression counts using the Cell Ranger software 10X Chromium Single Cell 3 provided by 10X Genomics. Briefly, raw BCL files from the Illumina HiSeq4000 were demultiplexed into paired-end GZIP-compressed FASTQ files using Cell Ranger’s mkfastq. Using Cell Ranger’s count, reads were aligned to the GRCh38 human reference genome and transcript counts were quantified for each annotated gene within each cell 7 . The resulting UMI count matrices (genes × cells) were provided as inputs to Seurat Suite (version 4.3.1) 8 . Expression matrix files for subsequent analyses were generated based on the gene and UMI counts. Cells were filtered using gene counts between 200 and 6,000, and UMI counts below 50,000. Cells with more than 20% mitochondrial content were excluded. Seurat functions were used for dimension reduction and clustering. All gene expression levels were normalized and scaled using NormalizeData and ScaleData. Dimension reduction and clustering We used principal component analysis (PCA) to analyze the top 2,000 variance genes, which were selected using FindVariableFeatures 9 . Clustering and visualization of the integrated dataset were performed using uniform manifold approximation and projection (UMAP), an unsupervised nonlinear dimensionality reduction technique, based on the first 20 principal components with a resolution of 0.4 (FindClusters and RunUMAP functions in Seurat). Cell cluster annotation We calculated the marker genes using the FindAllMarkers function with the Wilcox rank-sum test algorithm under the following criteria: 1) ln FC > 1, 2) adjusted p-value 0.01. Then, we identified the cell types and matched the marker genes of the corresponding cluster to specific cell types based on the “SingleR” 10 package and the CellMarker database 11 . GSEA Fifty classical gene sets downloaded from the GSEA website (GSEA | MSigDB [gsea-msigdb.org]) were used as references to further understand the biological functions of differentially expressed genes in different cell subtypes. Pathway analysis was used to identify significant pathways of marker genes and differentially expressed genes based on the KEGG database. Fisher’s exact test was used to select significant pathways, and the threshold of significance was defined by the P-value and FDR. Pseudo-time analysis Single-cell trajectory analysis was performed using Monocle2 12 (version 2.28.0) ( http://cole-trapnell-lab.github.io/monocle-release ) to reveal cell state transitions in the NP and immune cell clusters. Dimensional reduction and cell ordering were performed using the DDRTree method and the orderCells function. Before Monocle analysis, marker genes of the Seurat clustering results and raw expression counts of the filtered cells were selected. Cell communication analysis CellChat 13 (version 1.6.1) analysis was performed to assess cell-to-cell communication in whole-cell populations. CellChat is a tool for inferring and analyzing intercellular communication networks using network analysis and pattern recognition methods to predict the major signaling inputs and outputs of cells, and how these cells and signals coordinate their functions. CellChat assesses the impact of intercellular interactions based on intercellular ligand and receptor expression. We focused on the apparent differences in cellular ligand-receptor interactions during cellular communication between degenerated and healthy NP samples to explore the important role of cellular ligand-receptor interactions in IVDD. Significant means and cell communication significance (p < 0.05) were calculated based on the interaction and normalized cell matrix achieved by Seurat Normalization. Rats and treatment All rats used in this study were housed in a strictly pathogen-free environment. Sprague–Dawley rats were purchased from the Navy Medical University SPF Animal Laboratory (Shanghai, CHINA). A rat model of IVDD was generated by performing surgery under aseptic conditions. Briefly, the rats were placed in the prone position, the entire tail was shaved and cleaned (70% ethanol dissolved in double-distilled water), and a 1–1.5 cm longitudinal incision was made centered on the caudal vertebrae 6 and 7, and the skin was incised to expose the location of the intervertebral disc. Puncture with a 20-g needle was used to simulate disc degeneration in the rat caudal spine, and the skin was closed with a 4 − 0 silk suture. The control group did not undergo puncture.All animal experiments were conducted according to the guidelines approved by the Institutional Animal Care and Use Committee at the Navy Medical University. Magnetic resonance imaging (MRI) Two weeks after surgery, MRI was performed on all rats before sacrifice. After anesthetization, the rats were placed in a prone position with their spines straight. The degree of degeneration observed on MRI was determined according to the Pfirrmann grade by two spine surgeons. X-ray Two weeks after surgery, X-ray was performed on all rats before sacrifice. After anesthetization, the rats were placed in a prone position with their spines straight. Two Spine Surgeons Observe of intervertebral space height to determine disc degeneration. Immunohistochemistry (IHC) and histopathological analysis Tissue specimens were embedded in paraffin and cut into 5-µm sections. Subsequently, the sections were deparaffinized and rehydrated, followed by hematoxylin and eosin (H&E) and Safranin-O (S-O) staining, or antigen retrieval with 0.01 M sodium citrate. Sections were blocked with 3% hydrogen peroxide and 5% normal goat serum. The slides were then incubated with primary antibodies: included anti‐spp1 (30200-1-AP; Wuhan Sanying). The sections were incubated with a secondary antibody and developed using DAB solution. H&E was used for nuclear and cytoplasmic staining. Finally, the sections were observed and imaged under an Olympus BX63 microscope and a polarized microscope (Leica) at ×10, ×50, and ×400 magnification, and the expression of SPP1 + cells in the IVD samples was quantified using ImageJ software (National Institutes of Health). Histological scores were assigned to the normal and degenerated discs. NP cell culture The human NP cells used in the experiment were purchased from QuiCell. The cells were cultured in Complete medium for immortalised NP cells (QuiCell) at 37°C in 5% CO2. The medium was replaced twice weekly. NP cells were inoculated into six-well plates and cultured to 80% confluence for subsequent experiments. In vitro siRNA transfection Small interfering RNAs (Human SPP1 siRNA, targeting sequences #1 GTCTCACCATTCTGATGATGAA, #2 GAACGACTGATGATGTA, and #3 CCAAGTAAGTCCAACGAAA) were constructed by RiboBio and used to inhibit the expression of SPP1. NP cells were cultured in six-well plates to 60–70% confluence and transfected with negative control or SPP1 siRNA using Lipofectamine 3000 (Thermo Fisher Scientific) according to the manufacturer's instructions. After 48 h, cellular lysates were obtained to analyze the expression of the genes of interest. RNA isolation, complementary DNA (cDNA) synthesis, and real-time polymerase chain reaction (RT‐qPCR) Total RNA was isolated from NP tissues or cultured cells using the TRIzol reagent (TaKaRa Bio) according to the manufacturer's instructions. The RNA quantity was analyzed using a NanoDrop spectrophotometer (Thermo Fisher Scientific). mRNA was converted to cDNA using Prime Script RT Master Mix (TaKaRa). All reactions were run on a RT-PCR system (Applied Biosystems) and analyzed using the comparative Ct (ΔΔCt) method (2‐ΔΔCt with logarithmic transformation). The following primers were used: human SPP1 (F: 5′‐CTCCATTGACTCGAACGACTC‐3′, R: 5′‐CAGGTCTGCGAAACTTCTTAGAT‐3′); human GAPDH (F: 5′‐AATGGACAACTGGTCGTGGAC‐3′, R: 5′‐CCCTCCAGGGGATCTGTTTG‐3′). Western blot (WB) analysis The proteins of the treated NP cells were extracted and electrophoretically separated using 10% or 15% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Subsequently, the membranes were blocked with 3% bovine serum albumin (BSA) and incubated with primary antibodies. The primary antibodies included anti-SPP1 (30200-1-AP; Wuhan Sanying), anti-aggrecan (13880-1-AP; Wuhan Sanying), and anti‐MMP3(17873-1-AP; Wuhan Sanying). After washing with PBS, membranes were incubated with anti-rabbit IgG (7074; Cell Signaling Technology) or anti-mouse IgG (7076; Cell Signaling Technology) antibodies. Finally, the membrane was pressed in a dark room, exposed, and analyzed. Immunofluorescence (IF) NP cells were grown on confocal plates, incubated for 24 h, and then treated as needed for 24 h. Next, the cells were fixed for 15 min with 4% formalin and permeabilized for 10 min with 0.1% Triton X-100. After washing, cells were blocked for 1 h with 10% goat serum, incubated with diluted anti‐SPP1(30200-1-AP; Wuhan Sanying), anti‐aggrecan(13880-1-AP; Wuhan Sanying), and fluorescent secondary antibody, and observed under a fluorescence microscope. Results Identification and occupancy of IVDD NP cell subpopulations We analyzed scRNA sequencing data from the GSE199866 dataset, which included one healthy NP tissue and one degenerative NP tissue from the same person. After quality control and doublet exclusion filtering to remove cells with low gene detection ( 20%) (Fig. S1 A), 7633 cells from NP tissues were included in the study to provide a single-cell view of IVDD pathology. Using variance analysis, we acquired the top 2000 highly variable genes (Fig. S1 B). Next, we performed PCA to reduce the dimensions of the data. Subsequently, the UMAP algorithm was used to cluster the 20 principal components, and all cells were classified into seven cell clusters (Fig. S1 C). A heatmap illustrates the top 10 differential genes in each cell cluster (Fig. 1A). Cell clusters were annotated according to the cell marker database and published IVDD single-cell studies (Fig. 1B). NP cells were identified based on the levels of transcripts encoding different proteins [e.g., aggrecan proteoglycan (ACAN) and SRY-box transcription factor 9 (SOX9)] 14 (Fig. S1 D). In addition to NP cells, immune cells were identified in NP tissues (Cluster 6; expressing LZY , CXCL1 , and CD74 ) 15 , 16 (Fig. 1C). Six subpopulations were identified based on highly expressed genes and published single-cell data (Fig. 1C). 1) Adhesion NP cells (Cluster 1: mRNAs related to cell adhesion and migration such as FN1 17 and CRTAC1 18 ). 2) Homeostatic NP cells (Cluster 2; expressing RPS29 and RPS21 ); 19 3) Regulatory NP cells (Cluster 3: OGN 20 , CLEC3A 21 , and LECT1 22 ) 4) Effector NP cells (Cluster 4, expressing mRNAs that encode proteins that participate in cellular metabolic genes, e.g., MSMO 23 and HMGCS1 24 ); 5) Hypertrophic chondrocyte-like NP cells (HT-CLNPs; Cluster 5, expressing FRZB 25 ); 6) FibroNP cells (Cluster 6, expressing mRNAs that encode proteins related to fibrosis, COL1A1 and COL6A 19 , 26 ). Bar graphs show the number and percentage of all cell types in different NP samples (Fig. 1D, E). We found that immune cells were only present in degenerated NP tissues, and adhesion NP cells significantly increased in number and percentage as NP tissues degenerated and were the predominant cell type in degenerated NP tissues. In contrast, regulatory NP cells were the most common cell type in normal NP tissues. Functional enrichment analysis and pseudo-time analysis The biological functions of each cell subtype were analyzed using the ssGSEA algorithm with reference to a gene set of 50 HALLMARK biological pathways (Fig. 2A). Adhesion NP cells were mainly enriched in the TNFA_SIGNALING_VIA_NFKB signaling pathway, which is involved in the inflammatory response; regulatory NP cells were significantly enriched in the KRAS_ SIGNALING_DN pathway; effector NP cells were enriched in the MYOGENESIS and HEDGEHOG_SIGNALING pathways; fibroNP cells were mainly enriched in the SPERMATOGENESIS and E2F_TARGETS pathways. Immune cells were significantly enriched in the ALLOGRAFTREJECTION and IL6_JAK_STAT3_SIGNALING signaling pathways. In contrast, homeostatic NP cells and HT-CLNPs were not significantly enriched in any classical pathway. KEGG pathway enrichment showed that adhesion NP cells in degenerated tissues were enriched in the HIF-1 signaling pathway compared to those in healthy NP tissues, and that effector NP and fibro-NP cells were functionally similar and were enriched in cytoskeletal pathways, such as focal adhesion and regulation of the actin cytoskeleton. Homeostatic and regulatory NP cells were significantly enriched in mineral absorption pathways after degeneration (Fig. 2B). To study differentiation and corresponding gene expression in the different subpopulations, we selected all NP cell subpopulations and constructed a differentiation trajectory containing nine cell states (Fig. 2C, D). Most of the adhesion NP cells appeared in state 1, which is the beginning of the entire pseudotemporal differentiation, and the effector NP cells appeared mainly in states 6 and 7, which are the entire pseudotemporal differentiation at the end of pseudotemporal discretization. In addition, fibroNP cells showed a bipolar distribution in the differentiation trajectory, with a small fraction appearing at the beginning and most appearing at the end of the trajectory (Fig. 2E). CellChat analyses show cell-to-cell communication in NP To determine alterations in intercellular ligand/receptor interactions during degeneration, we used the CellChat algorithm to probe cellular communication in two NP samples with different degrees of degeneration. Comparison of Fig. 3A and B shows that intercellular communication was significantly increased after NP degeneration compared to that in healthy tissue; moreover, intercellular ligand/receptor interactions were altered, suggesting that immune cells infiltrating into the NP during degeneration have altered cellular communication compared to that in the original NP CellChat. Using weighted directed network measurements, we can separately identify the main senders of intercellular communication (senders), receivers (receivers), mediators (mediators), and influencers (influencers) of intercellular communication. The heatmap (Fig. 3C-E) visually demonstrates the changes in cellular communication in the NPs before and after degeneration. The increased cellular communication after degeneration mostly involves immune cells functioning as senders or receivers. The main cellular communication pathways in healthy NPs were the COLAGEN, FN1, and CD99 signaling pathway networks. whereas the SPP1 signaling pathway network was added to the degenerated NPs. To investigate the changes in the main cellular communications before and after degeneration, we listed FN1 and SPP1 individually in healthy and degenerated NPs(Fig. 3F-H). Owing to the addition of immune cells, the primary ligand emitters of the FN1 signaling pathway network changed from adhesion to regulatory NP cells, and fibro-NP cells, which are the primary mediator and effector pathways, changed to effector NP cells. Interaction did not change, and remained as FN1-CD44(Fig. S2). The SPP1 signaling pathway network is a major and unique intercellular communication pathway in degenerated NP. The SPP1 signaling pathway network ligands are mainly emitted by immune cells and act on the receptors of fibroNP cells, whereas adhesion NP cells mainly play a delivery role in this pathway (Fig. 4A, B). The SPP1 signaling pathway network consists of four major ligand/receptor interactions, the most prominent of which is SPP1-CD44 (Fig. 4C, D). The major expressed genes in the SPP1 signaling pathway network were represented in each cell subtype using violin plot, which showed that SPP1 was mainly expressed in degenerated NPs, and the expression of the most prominent receptor, CD44, was also significantly higher in degenerated NPs than in healthy NPs (Fig. 4E). SPP1 is involved in IVDD pathogenesis Considering the high expression of SPP1-related genes in patients with IVDD, we established an IVDD model using rat caudal intervertebral discs (Fig. 5A) to validate our scRNA-seq results. The MRI confirmed that the IVDD model was successfully established (Fig. 5B,C). X-ray showed a decrease in disc height after successful modelling (Fig. 5D). Dissection of the discs showed that the NP of healthy discs was hydrated, full, and translucent, whereas that of the degenerated discs was significantly shrunken, mineralized, and hardened (Fig. 5E). H&E and S-O staining were used to observe morphological changes in the intervertebral discs. The results showed that the height of the intervertebral discs, NP, and number of cells in IVDD rats were significantly reduced (Fig. 5F). In addition, the red area decreased and the green area increased, indicating a decrease in proteoglycan content in rats with IVDD (Fig. 5G), further confirming disc degeneration in our model rats. Immunohistochemical staining was performed to observe the expression of SPP1 in the healthy and degenerated intervertebral discs(Fig. 5H). We found that SPP1 levels were significantly elevated in the NP tissues of IVDD rats (p < 0.05) (Fig. 5I). This suggests that SPP1 accumulates in NP tissues of patients with IVDD and may be responsible for disc degeneration. To further investigate the relationship between SPP1 and IVDD, we used IL-1β stimulation to construct an NP cell degeneration model to simulate the infiltration and entry of immune cells after IVDD, and detected the expression of SPP1 and degeneration-related proteins by qrtPCR, western blotting, and immunofluorescence. The results showed that SPP1 expression was significantly higher compared to that in normal NP cells after different concentrations of IL-1β treatment (Fig. 6A). Western blot results showed that the expression of aggrecan gradually decreased with the increasing concentration of IL-1β, indicating that the degree of degeneration of NP cells increased with the increasing concentration of IL-1β (Fig. 6B,C). The expressions of SPP1 and aggrecan were completely opposite; the SPP1 increased in an IL-1β concentration-dependent manner (Fig. 6B,D). Immunofluorescence staining showed similar results. Using two representative concentrations of IL-1β (10 ng/ml and 50 ng/ml) to treat NP cells, we detected the immunofluorescence intensity of SPP1 expression, which was gradually increased, indicating that IL-1β significantly induced SPP1 expression in NP cells ( Fig. 6E). To further explore the role of SPP1 in IVDD, we measured the protein expression of aggrecan and MMP-3 in NP cells treated with different concentrations of SPP1 for 24 h (Fig. 6F-H). With increasing concentrations of SPP1, the expression of aggrecan in NP cells gradually decreased, and the expression of MMP-3 gradually increased, indicating that SPP1 significantly induced the degeneration of NP cells. The higher the concentration of SPP1, the more severe the degree of NP cell degeneration. The cells were fluorescently stained with phalloidin to observe their morphology. The results showed that compared with the control group, the fluorescence staining intensity of NP cells was lower after SPP1 stimulation, and the higher the concentration of SPP1, the greater the change in the morphology of NP cells, which were clearly elongated and exhibited a spindle shape (Fig. 6I). Compared with the NC group, both IL-1β 10 ng/ml and SPP1 50ng/ml led to a decrease in the expression of aggrecan fluorescence intensity in NP cells, indicating that both significantly induced the degeneration of NP cells (Fig. 6J). SPP1 may be a therapeutic target to reverse IVDD Three different siRNAs were designed for screening and qRT-PCR was used to detect SPP1 expression after transfection. The results showed that the expression of SPP1 was significantly reduced after SPP1-siRNA-1 and SPP1-siRNA-2 transfection, indicating that SPP1-siRNA-1 and SPP1-siRNA-2 were the most efficient in transfection (Fig. 7A). Western blot results (Fig. 7B) show that all three SPP1- siRNAs significantly inhibited the expression of SPP1 protein after transfection of human NP cells, and based on the statistical results (Fig. 7C), SPP1-siRNA-1 was the most effective. Combined with the qRT-PCR results, SPP1-siRNA-1 was finally selected for transfection of human NP cells to construct SPP1-silenced human NP cells for subsequent experiments. For the experiments, the cells were divided into 4 groups: control (normal myeloid cells, NC), degeneration (IL-1β 10 mg/ml), experimental (IL-1β 10ng/ml + SPP1-siRNA), and experimental control group (IL-1β 10ng/ml + NC-siRNA). After 24 h of treatment with IL-1β (10ng/ml), the cell growth of each group was observed using an inverted microscope (Fig. 7D). Compared with the control group, the number of cells in the degeneration group was significantly reduced and the cell morphology was more elongated. In the experimental group, the cell number and morphology were significantly better than those in the degeneration group (Fig. 7E-G). Due to SPP1 silencing in the experimental group, the expression of aggrecan protein was elevated compared with that in the degeneration group, and the expression of MMP-3 protein was reduced. This indicates that inhibition of SPP1 expression can improve the degeneration of myeloid cells. Phalloidin staining showed that the fluorescence staining intensity of NP cells in the degeneration group was the lowest, whereas that of the experimental group rebounded (Fig. 7H), which was similar to the WB results. The expression of aggrecan was elevated in NP cells after SPP1-siRNA transfection compared with the degeneration group (Fig. 7I). Discussion IDDD is common; therefore, finding effective and innovative treatments for to prevent or reverse IVDD and improve the clinical outcomes of patients is important 27 . An in-depth understanding of the biological basis and pathophysiological processes underlying IVDD is required to develop new therapeutic strategies 28 . However, owing to its complex multifactorial processes and cellular heterogeneity, the internal homeostasis and microenvironment of the IVD have not been fully elucidated. The NP, as one of the most critical components of the IVD, has osmotic properties owing to its richness in collagen type II (COL2) and aggrecan, and maintains its height and compressive strength by retaining more fluids, which play a physiological function in the IVD 6 . Therefore, focused on the NP and explored NP changes during disc degeneration. We analyzed two NP samples with different degrees of degeneration donated by the same patient based on public databases and obtained 7633 cellular scRNA-seq data points after QC. Unlike previous studies that included different inter-individual NP samples, the present study depicted NP cell profiles more precisely by comparatively analyzing different NP samples from the same individual, excluding the effects of individual differences such as age, sex, and disease. According to the results of our analysis, NP tissues contained two main types of NP cells and immune cells, and further downregulation and identification of NP cells identified six cell subtypes, namely adhesion, homeostatic, regulatory, effector, HT-CLNP, and fibroNP cells. TU 14 et al. reported a single-cell resolution transcriptional profile of human NP, which similarly identified six new human NP cell subtypes, which increases the credibility of the results of our analyses. In our analytical results, the proportion of adhesion NP cells was close to 50% and was the predominant cell subtype in degenerated NP. Adhesion NP cells were mainly enriched in the TNFA_SIGNALING_VIA_ NFKB signaling pathway, suggesting that they produce inflammatory factors, such as TNF-α, during IVDD, and are perhaps the NP cell subset that is mainly involved in inflammatory responses in causing NP degeneration. In addition, the inflammatory response accelerates disc degeneration by affecting NP cell metabolism and the extracellular matrix microenvironment and causes discogenic pain by promoting abnormal nerve ingrowth into the disc 29 . Thus, adhesion NP cells may be the NP cell subtype most strongly associated with pain. Regulation of glycolysis is mediated by hypoxia-inducible factor-1α (HIF-1α), a transcription factor that responds to local oxygen availability 30 . Adhesion NP cells in degenerated tissues were significantly enriched in the HIF-1 signaling pathway, suggesting that they are better adapted to the hypoxic environment than other NP cells. This explains why the number of adhesion NP cells increased rather than decreased with the number of degenerated cells in the disc. Fibro-NP cells, although relatively few, were the only other NP cell subtype with elevated cell numbers in degenerated NP. In pseudo-time analysis, the trajectory differentiation of FibroNP cells showed two levels of differentiation, with a small portion located in the initiation segment, indicating that they may have some myeloid progenitor cell characteristics. This finding is similar to that of Tu 14 et al., who reported that CD90 + fibroNP cells have myeloid progenitor cell characteristics. The NP progenitor cell properties of fibroNP cells may explain why their cell numbers increased rather than decreased in degenerated NP. Immune cells were only present in degenerated NP tissue, suggesting that immune cells were not originally present in the NP tissue but entered from outside the disc during degeneration. Ling et al. revealed the important role of macrophages in human disc degeneration in an scRNA-seq analysis 31 . The invasion of immune cells resulted in a marked enhancement of intercellular communication in NP tissues, adding a number of ligand/receptor signaling pathways that were not previously present, of which the SPP1 signaling pathway network was the most dominant. Based on cellular communication analysis 16 , Zhou et al. proposed that SPP1 is a new clue in the microenvironment of IVDD, which is related to the occurrence and degradation of IVD. SPP1, also known as osteobridging protein (OPN), is a transformation-associated phosphorylated protein found mainly in the extracellular matrix of mineralized tissues and in the extracellular fluid at sites of inflammation 32 . SPP1 binds to integrins and CD44, and plays a role in a variety of pathophysiological processes, including biomineralization, cellular immunity, inflammation, fibrosis, apoptosis, tumorigenesis, and metastasis 33 . Abnormal SPP1 expression is associated with a variety of skeletal disorders, and clinical studies have shown that serum SPP1 levels are positively correlated with the severity of osteoporosis and can be used as a biomarker for the early diagnosis of osteoporosis in postmenopausal women 34 . Many studies have found higher levels of SPP1 in the plasma and synovial fluid of patients with osteoarthritis than in healthy adults, indicating that SPP1 may be associated with the severity of osteoarthropathy. Studies on SPP1 in IVDD are still in their infancy. Gene profiling of human prominent IVD (H-IVD) and degenerative IVD (D-IVD) mesenchymal stem cells (MSCs) showed that D-IVD MSCs exhibited significant SPP1 overexpression compared to H-IVD-MSCs, and that SPP1 expression appeared to be directly correlated with its Thompson classification, suggesting that SPP1 may be a potential marker of IVD degeneration 35 . In our experiments, we found that IL-1β significantly induced the expression of SPP1 in NP cells, suggesting that the elevated expression of SPP1 may play a contributing role in the degeneration of NP. SPP1 is an important non-collagenous protein, which has a high affinity for type I collagen and hydroxyapatite, and is involved in the entire process of bone matrix mineralization 36 , 37 . This property of SPP1 may aggravate the mineralization of NP, causing them to lose their physiological functions and aggravating IVDD. To verify our hypothesis, we used SPP1 at different concentrations to stimulate NP cells, observed degeneration-related indices, and compared them with those of the control group. The results showed that SPP1 caused NP degeneration in a concentration-dependent manner. These experiments illustrate that elevated expression of SPP1 can lead to NP cell degeneration and that it is a key molecule in triggering NP degeneration. Based on the results of previous studies, we hypothesized that during disc degeneration, immune cells invade the interior of the NP via inflammatory chemotaxis and neovascularization. Immune cells that enter the interior of the NP act on the NP cells by secreting SPP1, generating a series of chain reactions that ultimately accelerate NP degeneration. To verify the above hypothesis, we constructed SPP1-silenced human NP cells by transiently transfecting human NP cells with siRNA to interfere with their SPP1 expression, and verified whether NP degeneration caused by IL-1β stimulation could be alleviated when SPP1 expression was reduced. In recent studies, SPP1 siRNA has been used to treat mice with rheumatoid arthritis, which resulted in a significant inhibition of synovial proliferation, leukocyte infiltration, and articular cartilage erosion. This indicated that SPP1 siRNA effectively mediated the depletion of SPP1, thereby inhibiting synovitis 38 . In our experiments, SPP1 siRNA effectively silenced the expression of SPP1 protein, and the degeneration of SPP1-silenced NP cells was significantly reduced in the experimental group compared to that in the degeneration group. This suggests that the inhibition of SPP1 expression ameliorated the degeneration of NP cells and that SPP1 may be a potential therapeutic target for blocking or reversing IVDD. The present study has some limitations. First, the sample size of scRNA-seq data is relatively small, and more healthy and degenerate samples are needed for comparative analyses in the future. Second, the NP cells were cultured on the surface of substrates rather than 3D culture, which cannot fully represent in vivo conditions. In addition, siRNA silencing of SPP1 for NP degeneration requires in vivo experimental validation. Conclusion Based on single-cell sequencing data, we revealed the changes in the NP cell atlas during IVDD and found that immune cells were only present in degenerated NP and that secreted SPP1 played a major role in cellular communication in degenerated NP. Thus, SPP1 may be a key molecule in NP degeneration. Subsequently, we experimentally verified that the expression of SPP1 was significantly elevated in a human NP degeneration model and caused the degeneration of human NP cells. Finally, silencing SPP1 expression using siRNA revealed that inhibition of SPP1 expression reversed the degeneration of NP cells. Our study suggests that SPP1 is a key molecule in the pathological process of IVDD, its expression level correlates with the severity of IVDD, and it may be a potential therapeutic target for blocking or reversing IVDD. Declarations Ethics approval and consent to participate All experimental protocols were approved by the Ethics Committee of Changhai hospital, Navy medical university Consent for publication No applicable. Availability of data and materials All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author. Competing interests The authors declare that they have no competing interests. Funding This study was supped by the Yuanhang Talent project of Navy medical university Author contributions LC, WXZ, ZXY, and LM designed the project. LC, LXY, and CYJ performed the experiments, statistical analysis, and drafted the manuscript. JK, DZX and WSH performed bioinformatics analyses. ZXY and WXZ helped to revise the manuscript. All authors have read and approved the final manuscript. Acknowledgements We thank SHANGHAI UNIVERSAL CLOUD MEDICAL IMAGING DIAGNOSTIC for supporting this study. References Balagué, F., Mannion, A.F., Pellisé, F., Cedraschi, C.: Non-specific low back pain. Lancet. 379 , 482–491 (2012). https://doi.org/10.1016/S0140-6736(11)60610-7 Cheng, X., Zhang, L., Zhang, K., Zhang, G., Hu, Y., Sun, X., Zhao, C., Li, H., Li, Y.M., Zhao, J.: Circular RNA VMA21 protects against intervertebral disc degeneration through targeting miR-200c and X linked inhibitor-of-apoptosis protein. Ann. Rheum. 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Cell. 26 , 99–105 (1981). https://doi.org/10.1016/0092-8674(81)90037-4 Murphy-Ullrich, J.E., Sage, E.H.: Revisiting the matricellular concept. Matrix Biol. 37 , 1–14 (2014). https://doi.org/10.1016/j.matbio.2014.07.005 Takanashi, M., Oikawa, K., Sudo, K., Tanaka, M., Fujita, K., Ishikawa, A., Nakae, S., Kaspar, R.L., Matsuzaki, M., Kudo, M., et al.: Therapeutic silencing of an endogenous gene by siRNA cream in an arthritis model mouse. Gene Ther. 16 , 982–989 (2009). https://doi.org/10.1038/gt.2009.66 Additional Declarations There is NO Competing Interest. Supplementary Files supplementarymaterial.docx supplemental meterial DBPRCOMMSBIO244159reportingsummary.pdf Reporting Summary Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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meterial","description":"","filename":"supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4737330/v1/4826b0f8ec75eb40135f9228.docx"},{"id":62983995,"identity":"9f901405-5861-468e-931d-829eb769d027","added_by":"auto","created_at":"2024-08-21 18:37:04","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1665688,"visible":true,"origin":"","legend":"Reporting Summary","description":"","filename":"DBPRCOMMSBIO244159reportingsummary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4737330/v1/5db867143c111b23c4938633.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Changes in nucleus pulposus cell atlas and the role of SPP1 during intervertebral disc degeneration: Single-cell sequencing analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eLow back pain (LBP) is a leading disabling health condition in humans, with a lifetime prevalence reaching up to 84%\u003csup\u003e1\u003c/sup\u003e Intervertebral disc degeneration (IVDD) is a widely recognized contributor to low back pain\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The current treatment of IVDD, mainly including bed rest, rehabilitation, medication, interventional therapy, and surgery\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, provides only symptomatic relief but fails to reestablish homeostasis of the intervertebral discs (IVDs). An increased understanding of human IVD physiology and pathology is necessary.\u003c/p\u003e \u003cp\u003eMature IVDs consist of a central nucleus pulposus (NP), surrounding annulus fibrosus (AF), and cartilage endplate (CEP), which adjoins the vertebra\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The origin of the IVD is heterologous; the NP is believed to be derived from the notochord, and the AF and CEP from the sclerotome\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The NP is rich in collagen type II (COL2) and proteoglycans. They facilitate osmotic properties and allow the retention of the fluid required to maintain the NP height and turgor against compressive loads\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Thus, it has been widely studied in IVDD.\u003c/p\u003e \u003cp\u003eCurrent studies on the pathophysiology of NP are supported by transcriptomic and epigenomic analyses. However, the development and application of single-cell sequencing technology can help explore the nature of the disease, reveal changes in NP cell types and intercellular communication during degeneration, and provide new ideas for the treatment of disc degeneration.\u003c/p\u003e \u003cp\u003eIn this study, we profiled 7633 cells from the NP of the same individual at different stages of degeneration. By analyzing single-cell sequencing data, we explored the cellular heterogeneity within the NP before and after degeneration and found that infiltration of immune cells into the interior of the NP affects intercellular crosstalk, with an important role played by the secreted phosphorylated protein 1 (SPP1) signaling pathway. Our results provide new cellular-level insights into the transcriptional alterations associated with IVDD, which could be used in the development of preventative and regenerative strategies for IVDD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSingle-cell RNA-seq data analysis\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eSingle-cell RNA-seq data processing\u003c/h2\u003e \u003cp\u003eUnbiased transcriptome-wide scRNA-seq and computational analyses were performed, and raw sequencing data for each sample were converted to matrices of expression counts using the Cell Ranger software 10X Chromium Single Cell 3 provided by 10X Genomics. Briefly, raw BCL files from the Illumina HiSeq4000 were demultiplexed into paired-end GZIP-compressed FASTQ files using Cell Ranger\u0026rsquo;s mkfastq. Using Cell Ranger\u0026rsquo;s count, reads were aligned to the GRCh38 human reference genome and transcript counts were quantified for each annotated gene within each cell\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The resulting UMI count matrices (genes \u0026times; cells) were provided as inputs to Seurat Suite (version 4.3.1)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Expression matrix files for subsequent analyses were generated based on the gene and UMI counts. Cells were filtered using gene counts between 200 and 6,000, and UMI counts below 50,000. Cells with more than 20% mitochondrial content were excluded. Seurat functions were used for dimension reduction and clustering. All gene expression levels were normalized and scaled using NormalizeData and ScaleData.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDimension reduction and clustering\u003c/h2\u003e \u003cp\u003eWe used principal component analysis (PCA) to analyze the top 2,000 variance genes, which were selected using FindVariableFeatures\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Clustering and visualization of the integrated dataset were performed using uniform manifold approximation and projection (UMAP), an unsupervised nonlinear dimensionality reduction technique, based on the first 20 principal components with a resolution of 0.4 (FindClusters and RunUMAP functions in Seurat).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCell cluster annotation\u003c/h2\u003e \u003cp\u003eWe calculated the marker genes using the FindAllMarkers function with the Wilcox rank-sum test algorithm under the following criteria: 1) ln FC\u0026thinsp;\u0026gt;\u0026thinsp;1, 2) adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and 3) min. pct\u0026thinsp;\u0026gt;\u0026thinsp;0.01. Then, we identified the cell types and matched the marker genes of the corresponding cluster to specific cell types based on the \u0026ldquo;SingleR\u0026rdquo; \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003epackage and the CellMarker database\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eGSEA\u003c/h2\u003e \u003cp\u003eFifty classical gene sets downloaded from the GSEA website (GSEA | MSigDB [gsea-msigdb.org]) were used as references to further understand the biological functions of differentially expressed genes in different cell subtypes. Pathway analysis was used to identify significant pathways of marker genes and differentially expressed genes based on the KEGG database. Fisher\u0026rsquo;s exact test was used to select significant pathways, and the threshold of significance was defined by the P-value and FDR.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePseudo-time analysis\u003c/h2\u003e \u003cp\u003eSingle-cell trajectory analysis was performed using Monocle2 \u003csup\u003e12\u003c/sup\u003e(version 2.28.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cole-trapnell-lab.github.io/monocle-release\u003c/span\u003e\u003cspan address=\"http://cole-trapnell-lab.github.io/monocle-release\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to reveal cell state transitions in the NP and immune cell clusters. Dimensional reduction and cell ordering were performed using the DDRTree method and the orderCells function. Before Monocle analysis, marker genes of the Seurat clustering results and raw expression counts of the filtered cells were selected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCell communication analysis\u003c/h2\u003e \u003cp\u003eCellChat \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e(version 1.6.1) analysis was performed to assess cell-to-cell communication in whole-cell populations. CellChat is a tool for inferring and analyzing intercellular communication networks using network analysis and pattern recognition methods to predict the major signaling inputs and outputs of cells, and how these cells and signals coordinate their functions. CellChat assesses the impact of intercellular interactions based on intercellular ligand and receptor expression. We focused on the apparent differences in cellular ligand-receptor interactions during cellular communication between degenerated and healthy NP samples to explore the important role of cellular ligand-receptor interactions in IVDD. Significant means and cell communication significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were calculated based on the interaction and normalized cell matrix achieved by Seurat Normalization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRats and treatment\u003c/h2\u003e \u003cp\u003eAll rats used in this study were housed in a strictly pathogen-free environment. Sprague\u0026ndash;Dawley rats were purchased from the Navy Medical University SPF Animal Laboratory (Shanghai, CHINA). A rat model of IVDD was generated by performing surgery under aseptic conditions. Briefly, the rats were placed in the prone position, the entire tail was shaved and cleaned (70% ethanol dissolved in double-distilled water), and a 1\u0026ndash;1.5 cm longitudinal incision was made centered on the caudal vertebrae 6 and 7, and the skin was incised to expose the location of the intervertebral disc. Puncture with a 20-g needle was used to simulate disc degeneration in the rat caudal spine, and the skin was closed with a 4\u0026thinsp;\u0026minus;\u0026thinsp;0 silk suture. The control group did not undergo puncture.All animal experiments were conducted according to the guidelines approved by the Institutional Animal Care and Use Committee at the Navy Medical University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMagnetic resonance imaging (MRI)\u003c/h2\u003e \u003cp\u003eTwo weeks after surgery, MRI was performed on all rats before sacrifice. After anesthetization, the rats were placed in a prone position with their spines straight. The degree of degeneration observed on MRI was determined according to the Pfirrmann grade by two spine surgeons.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eX-ray\u003c/h2\u003e \u003cp\u003eTwo weeks after surgery, X-ray was performed on all rats before sacrifice. After anesthetization, the rats were placed in a prone position with their spines straight. Two Spine Surgeons Observe of intervertebral space height to determine disc degeneration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry (IHC) and histopathological analysis\u003c/h2\u003e \u003cp\u003eTissue specimens were embedded in paraffin and cut into 5-\u0026micro;m sections. Subsequently, the sections were deparaffinized and rehydrated, followed by hematoxylin and eosin (H\u0026amp;E) and Safranin-O (S-O) staining, or antigen retrieval with 0.01 M sodium citrate. Sections were blocked with 3% hydrogen peroxide and 5% normal goat serum. The slides were then incubated with primary antibodies: included anti‐spp1 (30200-1-AP; Wuhan Sanying). The sections were incubated with a secondary antibody and developed using DAB solution. H\u0026amp;E was used for nuclear and cytoplasmic staining. Finally, the sections were observed and imaged under an Olympus BX63 microscope and a polarized microscope (Leica) at \u0026times;10, \u0026times;50, and \u0026times;400 magnification, and the expression of SPP1\u0026thinsp;+\u0026thinsp;cells in the IVD samples was quantified using ImageJ software (National Institutes of Health). Histological scores were assigned to the normal and degenerated discs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eNP cell culture\u003c/h2\u003e \u003cp\u003eThe human NP cells used in the experiment were purchased from QuiCell. The cells were cultured in Complete medium for immortalised NP cells (QuiCell) at 37\u0026deg;C in 5% CO2. The medium was replaced twice weekly. NP cells were inoculated into six-well plates and cultured to 80% confluence for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eIn vitro siRNA transfection\u003c/h2\u003e \u003cp\u003eSmall interfering RNAs (Human SPP1 siRNA, targeting sequences #1 GTCTCACCATTCTGATGATGAA, #2 GAACGACTGATGATGTA, and #3 CCAAGTAAGTCCAACGAAA) were constructed by RiboBio and used to inhibit the expression of SPP1. NP cells were cultured in six-well plates to 60\u0026ndash;70% confluence and transfected with negative control or SPP1 siRNA using Lipofectamine 3000 (Thermo Fisher Scientific) according to the manufacturer's instructions. After 48 h, cellular lysates were obtained to analyze the expression of the genes of interest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRNA isolation, complementary DNA (cDNA) synthesis, and real-time polymerase chain reaction (RT‐qPCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from NP tissues or cultured cells using the TRIzol reagent (TaKaRa Bio) according to the manufacturer's instructions. The RNA quantity was analyzed using a NanoDrop spectrophotometer (Thermo Fisher Scientific). mRNA was converted to cDNA using Prime Script RT Master Mix (TaKaRa). All reactions were run on a RT-PCR system (Applied Biosystems) and analyzed using the comparative Ct (ΔΔCt) method (2‐ΔΔCt with logarithmic transformation). The following primers were used: human SPP1 (F: 5\u0026prime;‐CTCCATTGACTCGAACGACTC‐3\u0026prime;, R: 5\u0026prime;‐CAGGTCTGCGAAACTTCTTAGAT‐3\u0026prime;); human GAPDH (F: 5\u0026prime;‐AATGGACAACTGGTCGTGGAC‐3\u0026prime;, R: 5\u0026prime;‐CCCTCCAGGGGATCTGTTTG‐3\u0026prime;).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot (WB) analysis\u003c/h2\u003e \u003cp\u003eThe proteins of the treated NP cells were extracted and electrophoretically separated using 10% or 15% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Subsequently, the membranes were blocked with 3% bovine serum albumin (BSA) and incubated with primary antibodies. The primary antibodies included anti-SPP1 (30200-1-AP; Wuhan Sanying), anti-aggrecan (13880-1-AP; Wuhan Sanying), and anti‐MMP3(17873-1-AP; Wuhan Sanying). After washing with PBS, membranes were incubated with anti-rabbit IgG (7074; Cell Signaling Technology) or anti-mouse IgG (7076; Cell Signaling Technology) antibodies. Finally, the membrane was pressed in a dark room, exposed, and analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence (IF)\u003c/h2\u003e \u003cp\u003eNP cells were grown on confocal plates, incubated for 24 h, and then treated as needed for 24 h. Next, the cells were fixed for 15 min with 4% formalin and permeabilized for 10 min with 0.1% Triton X-100. After washing, cells were blocked for 1 h with 10% goat serum, incubated with diluted anti‐SPP1(30200-1-AP; Wuhan Sanying), anti‐aggrecan(13880-1-AP; Wuhan Sanying), and fluorescent secondary antibody, and observed under a fluorescence microscope.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and occupancy of IVDD NP cell subpopulations\u003c/h2\u003e \u003cp\u003eWe analyzed scRNA sequencing data from the GSE199866 dataset, which included one healthy NP tissue and one degenerative NP tissue from the same person. After quality control and doublet exclusion filtering to remove cells with low gene detection (\u0026lt;\u0026thinsp;200 genes) and high mitochondrial gene content (\u0026gt;\u0026thinsp;20%) (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA), 7633 cells from NP tissues were included in the study to provide a single-cell view of IVDD pathology. Using variance analysis, we acquired the top 2000 highly variable genes (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). Next, we performed PCA to reduce the dimensions of the data. Subsequently, the UMAP algorithm was used to cluster the 20 principal components, and all cells were classified into seven cell clusters (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC). A heatmap illustrates the top 10 differential genes in each cell cluster (Fig.\u0026nbsp;1A). Cell clusters were annotated according to the cell marker database and published IVDD single-cell studies (Fig.\u0026nbsp;1B).\u003c/p\u003e \u003cp\u003eNP cells were identified based on the levels of transcripts encoding different proteins [e.g., aggrecan proteoglycan (ACAN) and SRY-box transcription factor 9 (SOX9)]\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD). In addition to NP cells, immune cells were identified in NP tissues (Cluster 6; expressing \u003cem\u003eLZY\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCD74\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;1C). Six subpopulations were identified based on highly expressed genes and published single-cell data (Fig.\u0026nbsp;1C).\u003c/p\u003e \u003cp\u003e1) Adhesion NP cells (Cluster 1: mRNAs related to cell adhesion and migration such as \u003cem\u003eFN1\u003c/em\u003e\u003csup\u003e17\u003c/sup\u003e and \u003cem\u003eCRTAC1\u003c/em\u003e\u003csup\u003e18\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e2) Homeostatic NP cells (Cluster 2; expressing \u003cem\u003eRPS29\u003c/em\u003e and \u003cem\u003eRPS21\u003c/em\u003e);\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e3) Regulatory NP cells (Cluster 3: \u003cem\u003eOGN\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eCLEC3A\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and \u003cem\u003eLECT1\u003c/em\u003e\u003csup\u003e22\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003e4) Effector NP cells (Cluster 4, expressing mRNAs that encode proteins that participate in cellular metabolic genes, e.g., \u003cem\u003eMSMO\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eHMGCS1\u003c/em\u003e\u003csup\u003e24\u003c/sup\u003e);\u003c/p\u003e \u003cp\u003e5) Hypertrophic chondrocyte-like NP cells (HT-CLNPs; Cluster 5, expressing \u003cem\u003eFRZB\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e);\u003c/p\u003e \u003cp\u003e6) FibroNP cells (Cluster 6, expressing mRNAs that encode proteins related to fibrosis, \u003cem\u003eCOL1A1\u003c/em\u003e and \u003cem\u003eCOL6A\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eBar graphs show the number and percentage of all cell types in different NP samples (Fig.\u0026nbsp;1D, E). We found that immune cells were only present in degenerated NP tissues, and adhesion NP cells significantly increased in number and percentage as NP tissues degenerated and were the predominant cell type in degenerated NP tissues. In contrast, regulatory NP cells were the most common cell type in normal NP tissues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis and pseudo-time analysis\u003c/h2\u003e \u003cp\u003eThe biological functions of each cell subtype were analyzed using the ssGSEA algorithm with reference to a gene set of 50 HALLMARK biological pathways (Fig.\u0026nbsp;2A). Adhesion NP cells were mainly enriched in the TNFA_SIGNALING_VIA_NFKB signaling pathway, which is involved in the inflammatory response; regulatory NP cells were significantly enriched in the KRAS_ SIGNALING_DN pathway; effector NP cells were enriched in the MYOGENESIS and HEDGEHOG_SIGNALING pathways; fibroNP cells were mainly enriched in the SPERMATOGENESIS and E2F_TARGETS pathways. Immune cells were significantly enriched in the ALLOGRAFTREJECTION and IL6_JAK_STAT3_SIGNALING signaling pathways. In contrast, homeostatic NP cells and HT-CLNPs were not significantly enriched in any classical pathway.\u003c/p\u003e \u003cp\u003eKEGG pathway enrichment showed that adhesion NP cells in degenerated tissues were enriched in the HIF-1 signaling pathway compared to those in healthy NP tissues, and that effector NP and fibro-NP cells were functionally similar and were enriched in cytoskeletal pathways, such as focal adhesion and regulation of the actin cytoskeleton. Homeostatic and regulatory NP cells were significantly enriched in mineral absorption pathways after degeneration (Fig.\u0026nbsp;2B).\u003c/p\u003e \u003cp\u003eTo study differentiation and corresponding gene expression in the different subpopulations, we selected all NP cell subpopulations and constructed a differentiation trajectory containing nine cell states (Fig.\u0026nbsp;2C, D). Most of the adhesion NP cells appeared in state 1, which is the beginning of the entire pseudotemporal differentiation, and the effector NP cells appeared mainly in states 6 and 7, which are the entire pseudotemporal differentiation at the end of pseudotemporal discretization. In addition, fibroNP cells showed a bipolar distribution in the differentiation trajectory, with a small fraction appearing at the beginning and most appearing at the end of the trajectory (Fig.\u0026nbsp;2E).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eCellChat analyses show cell-to-cell communication in NP\u003c/h2\u003e \u003cp\u003eTo determine alterations in intercellular ligand/receptor interactions during degeneration, we used the CellChat algorithm to probe cellular communication in two NP samples with different degrees of degeneration. Comparison of Fig.\u0026nbsp;3A and B shows that intercellular communication was significantly increased after NP degeneration compared to that in healthy tissue; moreover, intercellular ligand/receptor interactions were altered, suggesting that immune cells infiltrating into the NP during degeneration have altered cellular communication compared to that in the original NP CellChat. Using weighted directed network measurements, we can separately identify the main senders of intercellular communication (senders), receivers (receivers), mediators (mediators), and influencers (influencers) of intercellular communication. The heatmap (Fig.\u0026nbsp;3C-E) visually demonstrates the changes in cellular communication in the NPs before and after degeneration. The increased cellular communication after degeneration mostly involves immune cells functioning as senders or receivers. The main cellular communication pathways in healthy NPs were the COLAGEN, FN1, and CD99 signaling pathway networks. whereas the SPP1 signaling pathway network was added to the degenerated NPs. To investigate the changes in the main cellular communications before and after degeneration, we listed FN1 and SPP1 individually in healthy and degenerated NPs(Fig.\u0026nbsp;3F-H). Owing to the addition of immune cells, the primary ligand emitters of the FN1 signaling pathway network changed from adhesion to regulatory NP cells, and fibro-NP cells, which are the primary mediator and effector pathways, changed to effector NP cells. Interaction did not change, and remained as FN1-CD44(Fig. S2).\u003c/p\u003e \u003cp\u003eThe SPP1 signaling pathway network is a major and unique intercellular communication pathway in degenerated NP. The SPP1 signaling pathway network ligands are mainly emitted by immune cells and act on the receptors of fibroNP cells, whereas adhesion NP cells mainly play a delivery role in this pathway (Fig.\u0026nbsp;4A, B). The SPP1 signaling pathway network consists of four major ligand/receptor interactions, the most prominent of which is SPP1-CD44 (Fig.\u0026nbsp;4C, D). The major expressed genes in the SPP1 signaling pathway network were represented in each cell subtype using violin plot, which showed that SPP1 was mainly expressed in degenerated NPs, and the expression of the most prominent receptor, CD44, was also significantly higher in degenerated NPs than in healthy NPs (Fig.\u0026nbsp;4E).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eSPP1 is involved in IVDD pathogenesis\u003c/h2\u003e \u003cp\u003eConsidering the high expression of SPP1-related genes in patients with IVDD, we established an IVDD model using rat caudal intervertebral discs (Fig.\u0026nbsp;5A) to validate our scRNA-seq results. The MRI confirmed that the IVDD model was successfully established (Fig.\u0026nbsp;5B,C). X-ray showed a decrease in disc height after successful modelling (Fig.\u0026nbsp;5D). Dissection of the discs showed that the NP of healthy discs was hydrated, full, and translucent, whereas that of the degenerated discs was significantly shrunken, mineralized, and hardened (Fig.\u0026nbsp;5E). H\u0026amp;E and S-O staining were used to observe morphological changes in the intervertebral discs. The results showed that the height of the intervertebral discs, NP, and number of cells in IVDD rats were significantly reduced (Fig.\u0026nbsp;5F). In addition, the red area decreased and the green area increased, indicating a decrease in proteoglycan content in rats with IVDD (Fig.\u0026nbsp;5G), further confirming disc degeneration in our model rats. Immunohistochemical staining was performed to observe the expression of SPP1 in the healthy and degenerated intervertebral discs(Fig.\u0026nbsp;5H). We found that SPP1 levels were significantly elevated in the NP tissues of IVDD rats (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;5I). This suggests that SPP1 accumulates in NP tissues of patients with IVDD and may be responsible for disc degeneration.\u003c/p\u003e \u003cp\u003eTo further investigate the relationship between SPP1 and IVDD, we used IL-1β stimulation to construct an NP cell degeneration model to simulate the infiltration and entry of immune cells after IVDD, and detected the expression of SPP1 and degeneration-related proteins by qrtPCR, western blotting, and immunofluorescence. The results showed that SPP1 expression was significantly higher compared to that in normal NP cells after different concentrations of IL-1β treatment (Fig.\u0026nbsp;6A). Western blot results showed that the expression of aggrecan gradually decreased with the increasing concentration of IL-1β, indicating that the degree of degeneration of NP cells increased with the increasing concentration of IL-1β (Fig.\u0026nbsp;6B,C). The expressions of SPP1 and aggrecan were completely opposite; the SPP1 increased in an IL-1β concentration-dependent manner (Fig.\u0026nbsp;6B,D). Immunofluorescence staining showed similar results. Using two representative concentrations of IL-1β (10 ng/ml and 50 ng/ml) to treat NP cells, we detected the immunofluorescence intensity of \u003cem\u003eSPP1\u003c/em\u003e expression, which was gradually increased, indicating that IL-1β significantly induced \u003cem\u003eSPP1\u003c/em\u003e expression in NP cells ( Fig.\u0026nbsp;6E).\u003c/p\u003e \u003cp\u003eTo further explore the role of SPP1 in IVDD, we measured the protein expression of aggrecan and MMP-3 in NP cells treated with different concentrations of SPP1 for 24 h (Fig.\u0026nbsp;6F-H). With increasing concentrations of SPP1, the expression of aggrecan in NP cells gradually decreased, and the expression of MMP-3 gradually increased, indicating that SPP1 significantly induced the degeneration of NP cells. The higher the concentration of SPP1, the more severe the degree of NP cell degeneration. The cells were fluorescently stained with phalloidin to observe their morphology. The results showed that compared with the control group, the fluorescence staining intensity of NP cells was lower after SPP1 stimulation, and the higher the concentration of SPP1, the greater the change in the morphology of NP cells, which were clearly elongated and exhibited a spindle shape (Fig.\u0026nbsp;6I). Compared with the NC group, both IL-1β 10 ng/ml and SPP1 50ng/ml led to a decrease in the expression of aggrecan fluorescence intensity in NP cells, indicating that both significantly induced the degeneration of NP cells (Fig.\u0026nbsp;6J).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eSPP1 may be a therapeutic target to reverse IVDD\u003c/h2\u003e \u003cp\u003eThree different siRNAs were designed for screening and qRT-PCR was used to detect \u003cem\u003eSPP1\u003c/em\u003e expression after transfection. The results showed that the expression of \u003cem\u003eSPP1\u003c/em\u003e was significantly reduced after SPP1-siRNA-1 and SPP1-siRNA-2 transfection, indicating that SPP1-siRNA-1 and SPP1-siRNA-2 were the most efficient in transfection (Fig.\u0026nbsp;7A). Western blot results (Fig.\u0026nbsp;7B) show that all three SPP1- siRNAs significantly inhibited the expression of SPP1 protein after transfection of human NP cells, and based on the statistical results (Fig.\u0026nbsp;7C), SPP1-siRNA-1 was the most effective. Combined with the qRT-PCR results, SPP1-siRNA-1 was finally selected for transfection of human NP cells to construct SPP1-silenced human NP cells for subsequent experiments.\u003c/p\u003e \u003cp\u003eFor the experiments, the cells were divided into 4 groups: control (normal myeloid cells, NC), degeneration (IL-1β 10 mg/ml), experimental (IL-1β 10ng/ml\u0026thinsp;+\u0026thinsp;SPP1-siRNA), and experimental control group (IL-1β 10ng/ml\u0026thinsp;+\u0026thinsp;NC-siRNA). After 24 h of treatment with IL-1β (10ng/ml), the cell growth of each group was observed using an inverted microscope (Fig.\u0026nbsp;7D). Compared with the control group, the number of cells in the degeneration group was significantly reduced and the cell morphology was more elongated. In the experimental group, the cell number and morphology were significantly better than those in the degeneration group (Fig.\u0026nbsp;7E-G). Due to SPP1 silencing in the experimental group, the expression of aggrecan protein was elevated compared with that in the degeneration group, and the expression of MMP-3 protein was reduced. This indicates that inhibition of SPP1 expression can improve the degeneration of myeloid cells. Phalloidin staining showed that the fluorescence staining intensity of NP cells in the degeneration group was the lowest, whereas that of the experimental group rebounded (Fig.\u0026nbsp;7H), which was similar to the WB results. The expression of aggrecan was elevated in NP cells after SPP1-siRNA transfection compared with the degeneration group (Fig.\u0026nbsp;7I).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIDDD is common; therefore, finding effective and innovative treatments for to prevent or reverse IVDD and improve the clinical outcomes of patients is important\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. An in-depth understanding of the biological basis and pathophysiological processes underlying IVDD is required to develop new therapeutic strategies\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, owing to its complex multifactorial processes and cellular heterogeneity, the internal homeostasis and microenvironment of the IVD have not been fully elucidated. The NP, as one of the most critical components of the IVD, has osmotic properties owing to its richness in collagen type II (COL2) and aggrecan, and maintains its height and compressive strength by retaining more fluids, which play a physiological function in the IVD\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Therefore, focused on the NP and explored NP changes during disc degeneration. We analyzed two NP samples with different degrees of degeneration donated by the same patient based on public databases and obtained 7633 cellular scRNA-seq data points after QC. Unlike previous studies that included different inter-individual NP samples, the present study depicted NP cell profiles more precisely by comparatively analyzing different NP samples from the same individual, excluding the effects of individual differences such as age, sex, and disease. According to the results of our analysis, NP tissues contained two main types of NP cells and immune cells, and further downregulation and identification of NP cells identified six cell subtypes, namely adhesion, homeostatic, regulatory, effector, HT-CLNP, and fibroNP cells. TU\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e et al. reported a single-cell resolution transcriptional profile of human NP, which similarly identified six new human NP cell subtypes, which increases the credibility of the results of our analyses.\u003c/p\u003e \u003cp\u003eIn our analytical results, the proportion of adhesion NP cells was close to 50% and was the predominant cell subtype in degenerated NP. Adhesion NP cells were mainly enriched in the TNFA_SIGNALING_VIA_ NFKB signaling pathway, suggesting that they produce inflammatory factors, such as TNF-α, during IVDD, and are perhaps the NP cell subset that is mainly involved in inflammatory responses in causing NP degeneration. In addition, the inflammatory response accelerates disc degeneration by affecting NP cell metabolism and the extracellular matrix microenvironment and causes discogenic pain by promoting abnormal nerve ingrowth into the disc\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Thus, adhesion NP cells may be the NP cell subtype most strongly associated with pain. Regulation of glycolysis is mediated by hypoxia-inducible factor-1α (HIF-1α), a transcription factor that responds to local oxygen availability\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Adhesion NP cells in degenerated tissues were significantly enriched in the HIF-1 signaling pathway, suggesting that they are better adapted to the hypoxic environment than other NP cells. This explains why the number of adhesion NP cells increased rather than decreased with the number of degenerated cells in the disc. Fibro-NP cells, although relatively few, were the only other NP cell subtype with elevated cell numbers in degenerated NP. In pseudo-time analysis, the trajectory differentiation of FibroNP cells showed two levels of differentiation, with a small portion located in the initiation segment, indicating that they may have some myeloid progenitor cell characteristics. This finding is similar to that of Tu \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003eet al., who reported that CD90\u0026thinsp;+\u0026thinsp;fibroNP cells have myeloid progenitor cell characteristics. The NP progenitor cell properties of fibroNP cells may explain why their cell numbers increased rather than decreased in degenerated NP.\u003c/p\u003e \u003cp\u003eImmune cells were only present in degenerated NP tissue, suggesting that immune cells were not originally present in the NP tissue but entered from outside the disc during degeneration. Ling et al. revealed the important role of macrophages in human disc degeneration in an scRNA-seq analysis\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The invasion of immune cells resulted in a marked enhancement of intercellular communication in NP tissues, adding a number of ligand/receptor signaling pathways that were not previously present, of which the SPP1 signaling pathway network was the most dominant. Based on cellular communication analysis\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, Zhou et al. proposed that SPP1 is a new clue in the microenvironment of IVDD, which is related to the occurrence and degradation of IVD.\u003c/p\u003e \u003cp\u003eSPP1, also known as osteobridging protein (OPN), is a transformation-associated phosphorylated protein found mainly in the extracellular matrix of mineralized tissues and in the extracellular fluid at sites of inflammation\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. SPP1 binds to integrins and CD44, and plays a role in a variety of pathophysiological processes, including biomineralization, cellular immunity, inflammation, fibrosis, apoptosis, tumorigenesis, and metastasis\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Abnormal SPP1 expression is associated with a variety of skeletal disorders, and clinical studies have shown that serum SPP1 levels are positively correlated with the severity of osteoporosis and can be used as a biomarker for the early diagnosis of osteoporosis in postmenopausal women\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Many studies have found higher levels of SPP1 in the plasma and synovial fluid of patients with osteoarthritis than in healthy adults, indicating that SPP1 may be associated with the severity of osteoarthropathy. Studies on SPP1 in IVDD are still in their infancy. Gene profiling of human prominent IVD (H-IVD) and degenerative IVD (D-IVD) mesenchymal stem cells (MSCs) showed that D-IVD MSCs exhibited significant SPP1 overexpression compared to H-IVD-MSCs, and that SPP1 expression appeared to be directly correlated with its Thompson classification, suggesting that SPP1 may be a potential marker of IVD degeneration\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our experiments, we found that IL-1β significantly induced the expression of SPP1 in NP cells, suggesting that the elevated expression of SPP1 may play a contributing role in the degeneration of NP. SPP1 is an important non-collagenous protein, which has a high affinity for type I collagen and hydroxyapatite, and is involved in the entire process of bone matrix mineralization\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This property of SPP1 may aggravate the mineralization of NP, causing them to lose their physiological functions and aggravating IVDD. To verify our hypothesis, we used SPP1 at different concentrations to stimulate NP cells, observed degeneration-related indices, and compared them with those of the control group. The results showed that SPP1 caused NP degeneration in a concentration-dependent manner. These experiments illustrate that elevated expression of SPP1 can lead to NP cell degeneration and that it is a key molecule in triggering NP degeneration.\u003c/p\u003e \u003cp\u003eBased on the results of previous studies, we hypothesized that during disc degeneration, immune cells invade the interior of the NP via inflammatory chemotaxis and neovascularization. Immune cells that enter the interior of the NP act on the NP cells by secreting SPP1, generating a series of chain reactions that ultimately accelerate NP degeneration. To verify the above hypothesis, we constructed SPP1-silenced human NP cells by transiently transfecting human NP cells with siRNA to interfere with their SPP1 expression, and verified whether NP degeneration caused by IL-1β stimulation could be alleviated when SPP1 expression was reduced. In recent studies, SPP1 siRNA has been used to treat mice with rheumatoid arthritis, which resulted in a significant inhibition of synovial proliferation, leukocyte infiltration, and articular cartilage erosion. This indicated that SPP1 siRNA effectively mediated the depletion of SPP1, thereby inhibiting synovitis\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In our experiments, SPP1 siRNA effectively silenced the expression of SPP1 protein, and the degeneration of SPP1-silenced NP cells was significantly reduced in the experimental group compared to that in the degeneration group. This suggests that the inhibition of SPP1 expression ameliorated the degeneration of NP cells and that SPP1 may be a potential therapeutic target for blocking or reversing IVDD.\u003c/p\u003e \u003cp\u003eThe present study has some limitations. First, the sample size of scRNA-seq data is relatively small, and more healthy and degenerate samples are needed for comparative analyses in the future. Second, the NP cells were cultured on the surface of substrates rather than 3D culture, which cannot fully represent in vivo conditions. In addition, siRNA silencing of SPP1 for NP degeneration requires in vivo experimental validation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on single-cell sequencing data, we revealed the changes in the NP cell atlas during IVDD and found that immune cells were only present in degenerated NP and that secreted SPP1 played a major role in cellular communication in degenerated NP. Thus, SPP1 may be a key molecule in NP degeneration. Subsequently, we experimentally verified that the expression of SPP1 was significantly elevated in a human NP degeneration model and caused the degeneration of human NP cells. Finally, silencing SPP1 expression using siRNA revealed that inhibition of SPP1 expression reversed the degeneration of NP cells. Our study suggests that SPP1 is a key molecule in the pathological process of IVDD, its expression level correlates with the severity of IVDD, and it may be a potential therapeutic target for blocking or reversing IVDD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental protocols were approved by the Ethics Committee of Changhai hospital, Navy medical university\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this article.\u003c/p\u003e\n\u003cp\u003eFurther enquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supped by the Yuanhang Talent project of Navy medical university\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLC, WXZ, ZXY, and LM designed the project. LC, LXY, and CYJ performed the experiments, statistical analysis, and drafted the manuscript. JK, DZX and WSH performed bioinformatics analyses. ZXY and WXZ helped to revise the manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank SHANGHAI UNIVERSAL CLOUD MEDICAL IMAGING DIAGNOSTIC for supporting this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBalagu\u0026eacute;, F., Mannion, A.F., Pellis\u0026eacute;, F., Cedraschi, C.: Non-specific low back pain. 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Gene Ther. \u003cb\u003e16\u003c/b\u003e, 982\u0026ndash;989 (2009). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/gt.2009.66\u003c/span\u003e\u003cspan address=\"10.1038/gt.2009.66\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"scRNA-Seq, IVDD, nucleus pulposus, SPP1.","lastPublishedDoi":"10.21203/rs.3.rs-4737330/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4737330/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe nucleus pulposus (NP) plays a central role in the pathogenesis of intervertebral disc degeneration (IVDD); however, its internal cellular heterogeneity and molecular mechanisms have not yet been elucidated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eScRNA-seq was used to evaluate the structure of the NP at different degenerative stages in the same individual with IVDD. Unsupervised clustering of cells based on gene expression profiles was performed using the Seurat package and passed to Umap for cluster visualization. A rat disc degeneration model and an in vitro human NP cell degeneration model were established to validate the scRNA-Seq identification results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSix NP sub-clusters and immune cells were identified, and their distribution and functional differences between healthy and degenerative states were investigated. Immune cells were present only in degenerated NPs and may trigger NP degeneration. Cellular communication within the NP was altered by the intervention of immune cells. secreted phosphorylated protein 1 (SPP1), secreted by immune cells, plays a major role and is a key molecule in NP degeneration. The results of \u003cem\u003ein vivo\u003c/em\u003e animal experiments and \u003cem\u003ein vitro\u003c/em\u003e cellular experiments showed that the expression of SPP1 was increased in degenerating NPs. High expression of SPP1 promoted NP degeneration, whereas inhibition of its expression attenuated degeneration.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCytoarchitectural changes in NP were revealed by scRNA-Seq.\u0026nbsp;SPP1 is involved in the pathogenesis of disc degeneration and may be a new target for intervention in IVDD.\u003c/p\u003e","manuscriptTitle":"Changes in nucleus pulposus cell atlas and the role of SPP1 during intervertebral disc degeneration: Single-cell sequencing analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-21 18:36:59","doi":"10.21203/rs.3.rs-4737330/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"835d56d8-7e3a-419d-b2c4-240e04f52c72","owner":[],"postedDate":"August 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35146369,"name":"Biological sciences/Computational biology and bioinformatics/Data mining"},{"id":35146370,"name":"Biological sciences/Molecular biology/DNA damage and repair/Nucleotide excision repair"}],"tags":[],"updatedAt":"2024-08-30T13:05:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-21 18:36:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4737330","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4737330","identity":"rs-4737330","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}