Senescence and degeneration of human nucleus pulposus cells from in vivo and in vitro culture: A single-cell RNA sequencing study

Senescence and degeneration of human nucleus pulposus cells from in vivo and in vitro culture: A single-cell RNA sequencing study | 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 Research Article Senescence and degeneration of human nucleus pulposus cells from in vivo and in vitro culture: A single-cell RNA sequencing study Nixi Xu, Zhiyang Zhang, Yuanwu Cao, Zhe Wang, Chang Jiang, Yinglun Chen, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8901869/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Background Senescence and degeneration contribute to intervertebral disc disorders in the nucleus pulposus (NP) but are often conflated. This study aimed to delineate the distinct characteristics of senescence and degeneration in NP, examine the effects of in vitro culture on NP cells, and clarify the involvement of NP progenitor cells. Methods NP samples from six patients were analyzed by single-cell RNA sequencing, with p16 levels and Pfirrmann grades representing senescence and degeneration, respectively. Results NP cells were heterogeneous, including progenitor NP cells (ProNPC), regulatory NP cells (RegNPC), effector NP cells (EffNPC), homeostatic NP cells (HomoNPC), and fibrosis NP cells (FibroNPC). Senescence increased proliferation and immune activity, whereas degeneration decreased them; RegNPC was the most perturbed subtype. In vitro culture elevated p16 levels, primarily in ProNPC. In primary cells, the level of p16 in ProNPC decreased with degeneration, which was mainly mediated by E2F1 , whose level increased with degeneration. After culture, the proportion of macrophages was extremely low, with only ProNPC and FibroNPC remaining. Conclusions These findings indicated that senescence and degeneration are distinct, in vitro culture alters NP cell properties, and ProNPCs are closely associated with degeneration, as reflected in p16 expression patterns. Nucleus pulposus senescence Nucleus pulposus degeneration Intervertebral disc disorders Single-cell RNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Low back pain (LBP) is defined as pain or discomfort in the region between the lumbar and sacral spine [ 1 ]. It is often linked to sedentary lifestyle [ 2 ], physically demanding work [ 3 ], and obesity [ 4 ], and is increasingly observed in younger populations [ 5 ]. Among its etiologies, intervertebral disc (IVD) disorder, a common musculoskeletal degenerative disease, accounts for over 40% of all LBP cases [ 6 ]. IVD disorder is often characterized by structural disruption of the nucleus pulposus (NP), extracellular matrix (ECM) degradation, inflammation, and cell apoptosis [ 7 – 9 ]. These pathological changes in NP are largely driven by senescence and degeneration of NP [ 10 , 11 ]. Senescence represents an irreversible state of cells, marked by cell cycle arrest, a senescence-associated secretory phenotype (SASP), macromolecular damage, and metabolic dysfunction [ 12 ]. Degeneration, in contrast, refers to the progressive impairment of tissue or organ structure and function [ 13 ]. Generally, senescence and degeneration are regarded as distinct pathological processes in various fields, such as neurology and cardiovascular research [ 14 , 15 ]. However, they share many common features, including oxidative stress, mitochondrial dysfunction, and chronic inflammation [ 16 – 18 ]. In NP-related studies, this phenomenon is also observed, where senescence and degeneration mutually drive each other, ultimately resulting in ECM degradation and immune activation [ 19 ]. Interestingly, analysis of previous clinical NP samples [ 20 – 22 ] has revealed that the expression levels of senescence marker do not correlate linearly with Pfirrmann grading, suggesting that the extent of senescence and degeneration are not fully aligned. These findings raise the possibility that senescence and degeneration may represent two independent processes in NP pathology, and potentially in other disease contexts as well. Progenitor cells represent an intermediate stage between stem cells and fully differentiated cells, characterized by strong lineage-specific differentiation potential but relatively limited self-renewal capacity [ 23 ]. They have been identified across various systems, including neural progenitor cells (NPCs) [ 23 ], hematopoietic progenitor cells (HPCs) [ 24 ], and endothelial progenitor cells (EPCs) [ 25 ]. Progenitor cells contribute to regeneration and repair. For instance, in chronic spinal cord injury, transplanted NPCs have been shown to promote axonal regeneration [ 26 ]; following trauma, EPCs facilitate neovascularization and endothelial repair [ 27 ]. Progenitor cells have also been identified in the NP, where they can differentiate into NP cells with high ECM secretory capacity, promoting NP regeneration and representing a potential therapeutic approach for degenerated discs [ 28 ]. Beyond their roles in tissue regeneration and repair, progenitor cells exert critical functions in additional contexts. EPCs contribute to immunomodulation via the secretion of factors such as TNF-α, IL-1β, IL-6 and IL-8 [ 29 ]. EPCs facilitate vascular repair and confer therapeutic benefits in conditions including diabetes and myocardial infarction by releasing pro-angiogenic growth factors (VEGF, FGF, PDGF), and by producing vasoactive mediators, such as NO and ET-1, to maintain vascular homeostasis [ 30 ]. Moreover, in tuberous sclerosis complex, aberrant activation of the mTOR signaling pathway induces dysregulated proliferation and differentiation of NPCs, thereby exacerbating pathological progression [ 31 ]. Moreover, progenitor cells are closely associated with both senescence and degeneration. In murine progeria models, exogenous muscle-derived progenitor cells have been shown to delay aging [ 32 ]. In models of retinal degeneration and amyotrophic lateral sclerosis, NPCs secrete glial cell line-derived neurotrophic factor, providing neuroprotection and slowing the progression of neurodegenerative diseases [ 33 ]. In the NP, progenitor cells also play a critical role in senescence and degeneration. In many IVD disorder, a reduction of NP progenitor cells has been observed [ 34 ], and restoring their activity may help improve disc degeneration [ 35 ]. Moreover, the progression of IVD disorder is accompanied by senescence of NP progenitor cells, and mitigating the senescence of NP progenitor cells may contribute to slowing disease progression [ 36 ]. Single-cell RNA sequencing (scRNA-seq) is widely employed to elucidate intrinsic cellular heterogeneity and to identify novel cellular phenotypes, including in studies of the intervertebral disc (IVD) [ 37 ]. In this study, we aimed to investigate the distinct cellular features associated with senescence and degeneration in the NP, and to evaluate the impact of in vitro culture. Specifically, a particular focus was placed on the NP progenitor cells in the contexts of senescence, degeneration. Additional samples were assessed by flow cytometry, CCK-8 assays, and differentiation analyses to validate the scRNA-seq findings. This study sought to delineate the differences between senescence and degeneration, explore the effects of in vitro culture on NP cells, clarify the relationship between NP progenitor cells and these processes. Methods Human NP tissue collection NP samples were obtained from patients (Table 1 ) receiving open or endoscopic surgery. All the patients were informed consent. The study followed the Declaration of Helsinki and was approved by Ethics Committee. All patients received MRI examinations before surgery for evaluation of NP via the Pfirrmann grading system [ 38 ]. Table 1 Characteristics of the samples obtained from surgery No. Age Gender Pfirrmann Grade Location S1 23 Male Ⅱ L4/5 S2 32 Male Ⅲ L4/5 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 48 44 34 20 29 31 18 29 26 50 27 67 68 36 90 90 Male Male Female Male Male Male Male Female Male Female Male Male Male Female Male Male Ⅱ Ⅳ Ⅳ Ⅲ Ⅳ Ⅲ Ⅱ II II II III III III IV IV IV L5/S1 L5/S1 L5/S1 L4/5 L5/S1 L5/S1 L5/S1 L4/5 L4/5 L4/5 L5/S1 L4/5 L4/5 L5/S1 L4/5 L5/S1 Isolation and Adherent Culture of Human NP Cells NP samples were collected and put in a clean culture dish, then mechanically minced into small pieces (< 1 mm 3 ) and digested with 1mg/mL collagenase II (40508ES60, Yeasen Biotechnology Co., Ltd., Shanghai, China) at 37℃ for 3 hours. The primary cells were harvested using a 70 µm cell strainer (WHB Scientific, Shanghai, China), centrifuged at 1000 rpm for 5 minutes, and washed twice with phosphate buffered saline (PBS). The cells were resuspended in the Dulbecco’s modified eagle medium with low glucose (Biosharp Co., Ltd., Hefei, China) containing 10% fetal bovine serum (FBS) (OriCellTM, Cyagen Biosciences Co., Ltd., Guangzhou, China) and 1% penicillin-streptomycin solution (Keygen Biotech, Nanjing, China). The cells were transferred into T25 culture flasks (Corning, NY, USA) and cultured in a humidified incubator with 5% CO 2 at 37℃. Half of the supernatant was replaced with fresh medium on the third day. The whole supernatant was replaced every 3 days. Cells were collected using 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes. The primary cells isolated from three NP samples were passaged to obtain corresponding first-passage cells, using 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes (Table 1 ). ScRNA-seq Library Construction and Sequencing The libraries were prepared with Chromium Single cell 3’ Reagent v3 Kits (10× Genomics, Pleasanton, California, USA) according to the manufacturer’s protocol. Briefly, each single-cell suspension was mixed with primers, enzymes, and the gel beads containing barcode information, then loaded on a Chromium Single Cell Controller (10× Genomics) to generate single-cell gel beads in emulsions (GEMs). Each gel bead was bonded to one single cell and then wrapped with an oil surfactant. After generating the GEMs, reverse transcription was performed using barcoded full-length cDNA followed by the disruption of emulsions using the recovery agent and cDNA clean up with DynaBeads Myone Silane Beads (Thermo Fisher Scientific, Waltham, Massachusetts, USA). cDNA was then amplified by PCR with an appropriate number of cycles and thermal conditions that depended on the recovery cells. Subsequently, the amplified cDNA was fragmented, end-repaired, A-tailed, ligated to an index adaptor, and subjected to library amplification. The cDNA library was sequenced on a NovaSeq 6000 sequencer (Illumina, San Diego, California, USA). These procedures were performed by OE Biotech (OE Biotech Inc., Shanghai, China). Processing of ScRNA-seq Data The libraries were prepared with Chromium Single cell 3’ Reagent v3 Kits (10× Genomics, San Francisco, CA, USA) according to the manufacturer’s protocol. The cDNA library was sequenced on a NovaSeq 6000 sequencer (Illumina, CA, USA). The Cell Ranger software (version 6.1.2, 10× Genomics, San Francisco, CA, USA) was utilized for cellular barcode demultiplexing, read alignment to the genome and transcriptome using the STAR aligner, and read downsampling to produce normalized aggregated data across samples. This resulted in a gene-by-cell count matrix. Subsequent processing of the unique molecular identifier (UMI) count matrix was conducted using the package Seurat (version 4.2.0) [ 39 ] in R (version 4.2.2). Cells with UMI or gene counts deviating beyond two standard deviations from the mean were excluded. This approach assumes a Gaussian distribution and was used to eliminate low-quality cells and multiplets. The fraction of mitochondrial gene expression was examined to assess cell quality, and cells with mitochondrial gene contributions exceeding 10% of total counts were filtered out. The GRCh38 genome reference ( https://cf.10xgenomics.com/supp/cell-exp/refdata-gex-GRCh38-2020-A.tar.gz ) was employed for alignment. Library size normalization was performed using the NormalizeData function. Gene expression levels were normalized with the LogNormalize method, which scales the total expression for each cell by a default factor of 10,000 and applies log transformation to the data. Identification of Cell Types and Key Genes The batch effects in scRNA-seq data were removed using the Harmony algorithm (version 0.1.1) [ 40 ]. The FindClusters function in Seurat was used for cell clustering based on the gene expression profiles. Uniform manifold approximation and projection (UMAP) was used for data visualization via the RunUMAP function. Each cluster was manually identified based on the existing gene markers, which was verified by analyzing the genes and pathways. scRNA-seq data analysis was conducted using the R package SingleR (version 2.0.0) [ 41 ], a computational tool designed for unbiased cell type recognition. The cellular origins of the single cells and their respective cell types were identified using reference transcriptomic datasets from the Human Primary Cell Atlas (HPCA) and Blueprint. The following steps of the analysis were performed using Python (version 3.10.18). Differentially expressed genes (DEGs) were identified using the gene ranking method implemented in Scanpy (version 1.10.4) [ 42 ]. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using GSEAPy (version 1.1.8) [ 43 ]. Regulon activity of transcription factors (TF) was evaluated using pySCENIC (version 0.12.1) [ 44 ]. The cells most responsive to biological perturbations within the single-cell data were identified using the PertPy (version 0.11.5) [ 45 ]. Flow Cytometry and Cell Sorting Cells from three additional samples were cultured (Table 1 ). The adherent cultured cells were incubated with 20 µg/mL Hoechst 33342 (C1022, Beyotime Biotechnology, Nantong, China) in the dark at 37℃ for 30 minutes. The cells were then digested with 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes and resuspended in a concentration of 8 × 10 5 cells/mL. The cells were labeled with PE anti-human CD16 antibody (302008, Biolegend, CA, USA, 1:100) and APC anti-human CD26 Antibody (302709, Biolegend, San Diego, CA, USA, 1:100), then identified and sorted via flow cytometry using BD FACSAriaIII (BD Biosciences, CA, USA) following standard procedures. Macrophages and NP cells were labeled with CD16 and CD26, respectively. The sorted NP cells were further distinguished into G1 and G2/M phase cells via Hoechst 33342 staining to reflect the cell cycle. Four cell populations were obtained in each sample: G1 phase NP cells (CD26⁺/CD16⁻/Hoechst33342⁻), G2/M phase NP cells (CD26⁺/CD16⁻/Hoechst33342⁺), macrophages (CD26⁻/CD16⁺) and double negative cells (CD26⁻/CD16 − ). Three cell populations (G1 phase NP cells, G2/M phase NP cells, and macrophages) were sorted. Results NP Cells Exhibit Distinct Heterogeneity in Senescence and Degeneration We reviewed our previous clinical samples ( S10-S18 ) and found that Pfirrmann grades and H&E histological scores did not correlate with p16 level (Fig. 1 A). Consistently, public sequencing data [ 20 – 22 ] also showed no linear relationship between Pfirrmann grades and p16 level in NP samples ( Figure S1 A-C ). To further investigate the distinct features of senescence and degeneration in NP, six samples ( S1-S6 ) from six patients were analyzed by scRNA-seq (Fig. 1 B). The samples were divided into three p16 groups based on expression levels: low (0.017 ± 0.109), moderate (0.050 ± 0.193), and high (0.057 ± 0.244), as well as into three Pfirrmann groups (Grades II, III, and IV). (Table 1 , Figure S2 A, B ). The p16 and Pfirrmann level reflected the process of senescence and degeneration, respectively. First, the clusters were annotated as NP cells and immune cells via automated cell typing (Fig. 1 C). Cellular composition analysis illustrated that NP cells constituted the majority of the cellular population in NP tissue, and immune cells accounted for about 13.1% of all cells, suggesting that the environment of herniated NP was not immune-privileged. Interestingly, the proportion of immune cells increased with p16 level but decreased with Pfirrmann level. (Fig. 1 D, E). To further determine the subtypes, the NP cells were then re-clustered and manually annotated based on the existing cell annotation markers [ 46 – 48 ] (Table 2 ). The subtypes of NP cells were identified as progenitor NP cells (ProNPC, 2.7%), regulatory NP cells (RegNPC, 4.3%), effector NP cells (EffNPC, 60.2%), homeostatic NP cells (HomoNPC, 12.4%), and fibrosis NP cells (FibroNPC, 20.4%) (Fig. 1 F). The composition analysis indicated that EffNPC, FibroNPC, and HomoNPC constituted the majority of NP cells. The proportion of EffNPC increased with Pfirrmann level, while that of RegNPC decreased. However, the proportion of EffNPC and RegNPC across the p16 level showed opposite trends (Fig. 1 G, H). These results indicated the different cellular compositions between senescence and degeneration processes. Table 2 Marker genes of NP cells subtypes Subtype Marker ProNPC UBE2C, TOP2A RegNPC CHI3L1, CXCL2, NFKB1, CP, CXCL3, IL6 EffNPC HomoNPC FibroNPC MSMO1, HMGCS1 RPS29, RPS21 COL1A1, COL3A1, COL6A1, MMP2, FBLN1 NP Cells Exhibit Distinct Function in Senescence and Degeneration The cell cycle was determined to evaluate the growth status of cells. ProNPC exhibited proliferative status with S/G2 phases across each subtype, and other subtypes exhibited static status with G1/M phases (Fig. 2 A). The proliferative status, indicated by S/G2 phase, increased with p16 level but decreased with Pfirrmann level (Fig. 2 B, C). Similarly, GO terms across the two classifications were compared. The low group exhibited sterol metabolism features, the moderate group exhibited proliferative features, and the high group exhibited immune features (Fig. 2 D). However, the GO terms of immune were highly exhibited in Pfirrmann II group with low level. As the Pfirrmann level increasing, the Pfirrmann III and IV groups exhibited features of stress reaction (Fig. 2 E). Using the Augur algorithm, it was found that RegNPC showed the most pronounced perturbation effects in both senescence and degeneration (Fig. 2 F, H). RegNPC exhibited immune-related GO terms, which were upregulated during senescence but downregulated during degeneration (Fig. 2 G, I). P16 in ProNPC is associate with degeneration Building on the above results, the following study focuses on how the features of p16 are altered throughout senescence and degeneration. The primary and first-passage cell samples underwent scRNA-seq and clustering ( Figure S3 A ). After in vitro culture, UMAP and violin plots revealed that the first-passage NP cells had higher p16 expression (Fig. 3 A, B, D). ProNPC, which exhibited the most pronounced perturbation during culture, displayed the highest p16 expression levels among all subtypes in both primary and first-passage cells (Fig. 3 C–F). The p16 levels in ProNPC of primary cells were further investigated. It was found that p16 levels in ProNPC decreased during degeneration (Fig. 3 G), whereas no clear pattern was observed during senescence ( Figure S4 ). To explain this phenomenon, we sought to identify the related TFs. Accordingly, comparison of TF expression in ProNPC among different Pfirrmann groups revealed a subset of TFs with increased expression during degeneration (Fig. 3 H). Based on the AUC scores, which reflect TF regulatory activity, across the five NP cell subtypes, only E2F1 exhibited higher activity in ProNPC compared with the other subtypes (Fig. 3 I). The E2F1 level in ProNPC decreased after culture ( Figure S5 ). KEGG pathway analysis of E2F1 in ProNPC revealed its role in promoting the G1-to-S phase transition (Fig. 3 J), opposing the inhibitory function of p16 . These results suggest that E2F1 may be a potential factor underlying the decrease in p16 levels in ProNPC during degeneration. The Heterogeneity in the First-passage Cultured Cells According to the above results, cultured NP cells displayed features of senescence; however, the effects of culture on NP cells seem unlikely to be fully equivalent to those of senescence. To explore the effects of culture, the cellular heterogeneity of in vitro cultured cells was evaluated. Results showed that NP cells were the major cells (89.4% to 99.1%) during the culture while immune cells almost disappeared (10.6% to 0.9%) (Fig. 4 A, C). The subtype of first-passage cells was manually re-clustered while maintaining subtype annotations of primary cells (Fig. 4 B, D). Interestingly, only FibroNPC and ProNPC were detected after culture (Fig. 4 E), indicating that ProNPC and FibroNPC were the major subtypes of cultured NP cells. To verify the results of scRNA-seq analysis, flow cytometry was performed on another three NP samples ( Figure S3 B ), which showed that the composition of the first-passage cells included NP cells and a few macrophages (0.23%-2.96%) (Fig. 4 F, G). The G2/M phase cells, which were tried to identify ProNPC, had a higher proportion in the group with low senescence and degeneration (Fig. 4 H). Proliferative and Stemness Capacity of Different Cell Populations from NP The results of CCK-8 showed that the G2/M phase NP cells exhibited the highest proliferative capacity (Fig. 5 A). After the osteogenic and adipogenic differentiation induction in G1 and G2/M phase NP cells, Alizarin Red staining and Oil Red O staining revealed red calcium nodules and lipid droplets of varying sizes after osteogenic induction and adipogenic induction, respectively (Fig. 5 B). However, the staining showed no significant difference between G1 and G2/M phase NP cells (Fig. 5 C, D). The expression of osteogenic genes ( ALP and OC ) and adipogenic genes ( APP and LPL ) was significantly increased in the G1 phase NP cells (Fig. 5 E, F). These results of induction indicated the differentiation potential in the cultured NP cells. Discussion Senescence and degeneration, as distinct pathological processes, displayed divergent features, particularly in immune activity. In our study, increased immune activity was the most notable characteristic of senescence. During senescence, NP exhibited an accumulation of immune cells, along with a function transition from metabolism and proliferation to immune and inflammatory. RegNPC, the immune-related subtype of NP, expanded during senescence and exhibited increased immune-related functions. During degeneration, immune activity was observed to decrease. However, previous studies have generally characterized degeneration as a process accompanied by immune activity [ 46 , 49 ]. We speculate that this discrepancy may be due to the relatively low survival capacity of immune cells, which leads to their loss during degeneration-induced cellular damage, thereby reducing overall immune activity. The proliferation, as reflected by the S/G2 phase, increased as a compensatory response during senescence, but reduced with degeneration-induced damage. EffNPC proportion decreased during senescence, likely due to overall metabolic downregulation in NP, whereas it increased during degeneration, possibly reflecting their high viability. The characteristics of ProNPC, the progenitor cells of the NP, changed during senescence and degeneration, as reflected by alterations in their p16 levels. P16 is a cell cycle regulatory protein and a widely recognized marker of senescence [ 50 ]. ProNPC is a p16 -enriched subtype; even when other subtypes in primary cells exhibit low p16 expression, ProNPC maintains high p16 levels. Despite its high proliferative capacity, ProNPC exhibits high expression of a senescence-associated molecule, which is seemingly contradictory. This paradox may be explained by the active cell cycle progression in ProNPC, predominantly in S and G2 phases, where p16 , as a G1-to-S phase inhibitor [ 51 ], could be upregulated compensatory, resulting in its high expression in this proliferative subtype. Our study showed that overall p16 levels in NP exhibited no clear pattern of change during degeneration. However, p16 levels in ProNPC declined with degeneration, a phenomenon that may be explained by E2F1 . E2F1 , a transcription factor highly active in ProNPC, also serves as a key regulator of the cell cycle [ 52 ]. E2F1 acts in opposition to p16 by promoting the G1-to-S phase transition in the cell cycle [ 52 ]. An antagonistic effect of E2F1 on p16 has been reported in previous studies, mainly in cell cycle regulation [ 53 , 54 ]. In ProNPC, E2F1 is upregulated during degeneration, which may antagonize p16 and leading to its downregulation. In addition, elevated E2F1 promotes cellular stress and apoptosis, further exacerbating cell damage during degeneration. With increasing passage in vitro , cells inevitably undergo senescence. However, the impact of culture on NP cells is clearly not equivalent to that of senescence. On the one hand, unlike senescence, which enhances immune activity, the proportion of immune cells in NP decreased after culture, likely due to their limited proliferative capacity. On the other hand, culture appeared to establish a dynamic balance between proliferation and homeostasis in first-passage cells. ProNPC, with their proliferative potential, sustain the cell population, whereas FibroNPC contribute to homeostasis by participating in ECM organization and senescence [ 33 ]. These findings suggest that FibroNPC may be a source of ECM supply. However, this study had some limitations. First, the study had a small sample size, and thus studies with larger sample sizes were needed to validate the findings. Also, some double-negative cells (CD26 − /CD16 − ) in NP were detected via flow cytometry. These cells were unexpected since most cells were already labeled with either CD26 or CD16. This could indicate that the markers of some cells were intracellular during the staining, leading to double-negative cells. Lastly, further studies were needed to verify the outcome of scRNA-seq. Besides, we needed to sort the subtypes more precisely via flow cytometry. Conclusion In conclusion, senescence and degeneration represent distinct pathological processes. Through scRNA-seq, this study clarifies the previously conflated concepts of senescence and degeneration, and reveals the impact of in vitro culture on NP cells. Moreover, it underscores that NP progenitor cells exhibit associations with degeneration through the p16 expression pattern. Abbreviations ECM Extracellular Matrix EPCs Endothelial Progenitor Cells GEMs Gel Beads in Emulsions GO Gene Ontology HPCs Hematopoietic Progenitor Cells IVD Intervertebral Disc KEGG Kyoto Encyclopedia of Genes and Genomes LBP Low Back Pain NP Nucleus Pulposus NPCs Neural Progenitor Cells PBS Phosphate Buffered Saline SASP Senescence—Associated Secretory Phenotype scRNA seq —Single—cell RNA Sequencing TFs Transcription Factors UMI Unique Molecular Identifier Declarations Ethics approval and consent to participate This study was approved by the Zhongshan Hospital Fudan University Ethics Committee (B2019-178). Written informed consent was obtained from all participants. Consent for publication Not applicable. Competing Interests The authors declare no conflict of interest. Funding This work was supported by the Featured Clinical Discipline Project of Shanghai Pudong New District (Pwyts2021-03); National Natural Science Foundation of China (Grant Number: 82001471); and Natural Science Foundation of Fujian (Grant Number: 2024J01320364). Author Contribution Study design: Nixi Xu, Zhe Wang, Lixia Jin, Zixian Chen and Xiuhui WangConducting experiments: Nixi Xu, Zhiyang Zhang, Yinglun Chen, Xinxin Liu and Zheng LiAcquiring data: Yuanwu Cao, Chang Jiang, Zengxin Jiang, Hongping Shan and Xiaoxing JiangAnalysing data: Nixi Xu, Zhiyang Zhang and Chang JiangWriting the manuscript: Nixi Xu, Zhe Wang and Chang JiangReviewing the manuscript: all authors Acknowledgments We thank OE Biotech and Dr. Xiang Li for their support in bioinformatics analysis. We thank Dr. Jianming Zeng (University of Macau), and all the members of his bioinformatics team, biotrainee, for generously sharing their experience and codes. Data Availability The data of single cell sequencing collected in this study are available in National Omics Data Encyclopedia (NODE) for everyone, by the URL of https://www.biosino.org/node/project/detail/OEP001692. The analysis code needs to be requested from the corresponding authors. References Morgan T, Wu J, Ovchinikova L, Lindner R, Blogg S, Moorin R. A national intervention to reduce imaging for low back pain by general practitioners: a retrospective economic program evaluation using Medicare Benefits Schedule data. BMC Health Serv Res. 2019;19:983. https://doi.org/10.1186/s12913-019-4773-y . Alzahrani H, Alshehri MA, Alzhrani M, Alshehri YS, Al Attar WSA. The association between sedentary behavior and low back pain in adults: a systematic review and meta-analysis of longitudinal studies. PeerJ. 2022;10:e13127. https://doi.org/10.7717/peerj.13127 . Nieminen LK, Pyysalo LM, Kankaanpää MJ. Prognostic factors for pain chronicity in low back pain: a systematic review. 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14:09:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8901869/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8901869/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104554727,"identity":"1f5c400d-7fd0-4ecf-bb16-2ba076476bb9","added_by":"auto","created_at":"2026-03-13 08:57:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11548058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct cell types and subtypes in human NP. \u003c/strong\u003e(A) MRI T2-weighted images, H\u0026amp;E, and \u003cem\u003ep16\u003c/em\u003e immunohistochemical staining of NP samples (\u003cstrong\u003eS10-S18\u003c/strong\u003e). (B) Schematic of workflow. (C) UMAP showing the NP cells and immune cells identified from all the cells. (D, E) The proportions of NP cells and immune cells from each age (D) and Pfirrmann (E) group. (F) UMAP showing the subtypes identified from NP cells. (G, H) The proportion of each NP subtype from each age (G) and Pfirrmann (H) group. H\u0026amp;E, Hematoxylin and Eosin; MRI, magnetic resonance imaging; NP, nucleus pulposus; ScRNA-seq, single cell RNA sequencing; UMAP, uniform manifold approximation and projection.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/10a0e930a81173f813d6ab92.png"},{"id":104554777,"identity":"08cc76a1-0d4c-4936-9bef-a4f507cdf861","added_by":"auto","created_at":"2026-03-13 08:58:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":8107399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct function of NP cells in senescence and degeneration.\u003c/strong\u003e(A-C) The proportion of each cell cycle (G1, S, G2, M phase) from each NP subtype (A), age group (B) and Pfirrmann group (C). (D, E) Bar chart showing the GOBP terms of each age group (D) and Pfirrmann group (E). (F, H) UMAP showing the distribution of Augur score in each subtype from age (F) and Pfirrmann (H) classification. (G, I) Bar chart showing the RegNPC upregulated GO terms from each age group (G) and Pfirrmann group (I). NP, nucleus pulposus; GOBP, gene ontology biological process; RegNPC, regulatory nucleus pulposus cells; UMAP, uniform manifold approximation and projection.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/040b76afb4920c9f014c1cf6.png"},{"id":104554811,"identity":"a1e208df-5ca1-4354-8c8a-58a414f573b2","added_by":"auto","created_at":"2026-03-13 08:58:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10263394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep16\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eduring senescence and degeneration.\u003c/strong\u003e(A, B) The distribution (A) and expression level (B) of \u003cem\u003ep16\u003c/em\u003e in primary cells and first-passage cells. (C) UMAP showing the distribution of Augur score associated with culture in both primary cells and first-passage cells. (D) The \u003cem\u003ep16\u003c/em\u003e expression levels of each subtype, in primary cells and first-passage NP cells. (E, F) The \u003cem\u003ep16\u003c/em\u003edistribution (E) and expression (F) of each subtype in primary cells. (G) The \u003cem\u003ep16\u003c/em\u003eexpression levels of ProNPC across different Pfirrmann groups. (H) The expression of all the TFs in ProNPC across different Pfirrmann groups. (I) TFs from ProNPC increasing with Pfirrmann grade were compared across each subtype by their AUC scores. (J) Significant KEGG pathways associated with \u003cem\u003eE2F1\u003c/em\u003ein ProNPC. AUC, Area Under the Curve for geneset enrichment; KEGG, Kyoto Encyclopedia of Genes and Genomes; NP, nucleus pulposus; ProNPC, progenitor nucleus pulposus cells; TFs, Transcription Factors; UMAP, uniform manifold approximation and projection.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/748b9dcf11fb4147716b4689.png"},{"id":104554745,"identity":"710684de-043d-4df7-b951-493c0fef037f","added_by":"auto","created_at":"2026-03-13 08:58:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":11534841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics of cells in NP after \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eculture.\u003c/strong\u003e (A) UMAP showing the NP cells and immune cells identified from all cells. (B) UMAP showing the primary and first-passage cells in all NP cells. (C) The proportions of NP cells and immune cells from primary and first-passage cells. (D) UMAP showing each subtype from both primary and first-passage cells. (E) The proportion of each subtype from primary and first-passage cells. (F) Flow cytometry analysis of cells, with marker of CD26, CD16 and Hoechst33342. (G) The proportion of each cell type from each sample. (H) The proportion of G1 and G2/M phase in NP cells from each sample. CD16, cluster of differentiation 16; CD26, cluster of differentiation 26; NP, nucleus pulposus; UMAP, uniform manifold approximation and projection;\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/0ed1085eb2170af5a81534df.png"},{"id":104554792,"identity":"38e6d235-1d84-473d-8584-8778172b954e","added_by":"auto","created_at":"2026-03-13 08:58:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6180144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProliferation and differentiation of sorted cells.\u003c/strong\u003e(A) Bar chart showing the 450nm OD values of G1 phase NP cells, G2/M phase NP cells and macrophages (n=10). (B) Alizarin Red S and Oli Red O staining of G1 phase NP cells and G2/M phase NP cells after 3-week osteogenesis and adipogenesis differentiation (Scale bar = 50 μm, n=4). (C, D) Bar chart showing the percentage of stained area of osteogenesis (C) and adipogenesis (D) differentiation in each type of cells (n=4). (E, F) Bar chart showing the relative gene expression of \u003cem\u003eALP, OC\u003c/em\u003e (E) and \u003cem\u003eAPP, LPL\u003c/em\u003e (F) in each type of cells (n=3). ALP, alkaline phosphatase; APP, adipogenic protein; LPL, lipoprotein lipase; NP, nucleus pulposus; OD, optical density; OC, osteocalcin. Data are represented as the mean ± standard deviation. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01; ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; ****\u003cem\u003eP\u003c/em\u003e\u0026lt;0.0001; ns, not statistically significant. \u003cem\u003eP \u003c/em\u003evalues were determined by one-way ANOVA with a Tukey's multiple comparisons test.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/283835ab1c8527dee17be702.png"},{"id":104835373,"identity":"6cd53d5f-3a3c-4157-a76b-2ef59dad480d","added_by":"auto","created_at":"2026-03-17 17:44:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":67109548,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/b4713a5f-1970-44cf-ba68-6cb955a1db8c.pdf"},{"id":104554705,"identity":"5d5256e0-810a-4c98-a968-9f7684901243","added_by":"auto","created_at":"2026-03-13 08:57:50","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":233514,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS5.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/20ab60fefa579b23c834a98b.tiff"},{"id":104554789,"identity":"6f165c39-405b-43c9-8d46-438a1e9a7ff4","added_by":"auto","created_at":"2026-03-13 08:58:06","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":240968,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/047390b91462f385acdd1454.tiff"},{"id":104554724,"identity":"09a2cc12-65d3-4260-a80f-484596397115","added_by":"auto","created_at":"2026-03-13 08:57:58","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":677613,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/ae4566d9fcb48851d662e91d.tiff"},{"id":104554783,"identity":"19a3ff44-12f4-437e-896e-d3024fa6f8f8","added_by":"auto","created_at":"2026-03-13 08:58:04","extension":"tiff","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":769405,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/3f4b82a98c15ede2c7e75244.tiff"},{"id":104554740,"identity":"63634588-8a05-45f7-8c89-6d03436fd3de","added_by":"auto","created_at":"2026-03-13 08:58:01","extension":"tiff","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1444804,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/d9a10bea94342f4457ae3f5f.tiff"},{"id":104554703,"identity":"977dd9cf-b1f0-4b83-b334-09058eebae1a","added_by":"auto","created_at":"2026-03-13 08:57:49","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":20295,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/764671e32cfe63ddebc1b161.docx"},{"id":104781449,"identity":"3d88b838-2959-44dd-a3a7-20c52c8f104d","added_by":"auto","created_at":"2026-03-17 07:55:41","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":27562,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8901869/v1/05d8d30f2c64b58965c34566.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Senescence and degeneration of human nucleus pulposus cells from in vivo and in vitro culture: A single-cell RNA sequencing study","fulltext":[{"header":"Background","content":"\u003cp\u003eLow back pain (LBP) is defined as pain or discomfort in the region between the lumbar and sacral spine [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is often linked to sedentary lifestyle [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], physically demanding work [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and obesity [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and is increasingly observed in younger populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Among its etiologies, intervertebral disc (IVD) disorder, a common musculoskeletal degenerative disease, accounts for over 40% of all LBP cases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIVD disorder is often characterized by structural disruption of the nucleus pulposus (NP), extracellular matrix (ECM) degradation, inflammation, and cell apoptosis [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These pathological changes in NP are largely driven by senescence and degeneration of NP [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Senescence represents an irreversible state of cells, marked by cell cycle arrest, a senescence-associated secretory phenotype (SASP), macromolecular damage, and metabolic dysfunction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Degeneration, in contrast, refers to the progressive impairment of tissue or organ structure and function [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Generally, senescence and degeneration are regarded as distinct pathological processes in various fields, such as neurology and cardiovascular research [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, they share many common features, including oxidative stress, mitochondrial dysfunction, and chronic inflammation [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In NP-related studies, this phenomenon is also observed, where senescence and degeneration mutually drive each other, ultimately resulting in ECM degradation and immune activation [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Interestingly, analysis of previous clinical NP samples [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] has revealed that the expression levels of senescence marker do not correlate linearly with Pfirrmann grading, suggesting that the extent of senescence and degeneration are not fully aligned. These findings raise the possibility that senescence and degeneration may represent two independent processes in NP pathology, and potentially in other disease contexts as well.\u003c/p\u003e \u003cp\u003eProgenitor cells represent an intermediate stage between stem cells and fully differentiated cells, characterized by strong lineage-specific differentiation potential but relatively limited self-renewal capacity [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. They have been identified across various systems, including neural progenitor cells (NPCs) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], hematopoietic progenitor cells (HPCs) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and endothelial progenitor cells (EPCs) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Progenitor cells contribute to regeneration and repair. For instance, in chronic spinal cord injury, transplanted NPCs have been shown to promote axonal regeneration [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]; following trauma, EPCs facilitate neovascularization and endothelial repair [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Progenitor cells have also been identified in the NP, where they can differentiate into NP cells with high ECM secretory capacity, promoting NP regeneration and representing a potential therapeutic approach for degenerated discs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond their roles in tissue regeneration and repair, progenitor cells exert critical functions in additional contexts. EPCs contribute to immunomodulation via the secretion of factors such as TNF-α, IL-1β, IL-6 and IL-8 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. EPCs facilitate vascular repair and confer therapeutic benefits in conditions including diabetes and myocardial infarction by releasing pro-angiogenic growth factors (VEGF, FGF, PDGF), and by producing vasoactive mediators, such as NO and ET-1, to maintain vascular homeostasis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, in tuberous sclerosis complex, aberrant activation of the mTOR signaling pathway induces dysregulated proliferation and differentiation of NPCs, thereby exacerbating pathological progression [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, progenitor cells are closely associated with both senescence and degeneration. In murine progeria models, exogenous muscle-derived progenitor cells have been shown to delay aging [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In models of retinal degeneration and amyotrophic lateral sclerosis, NPCs secrete glial cell line-derived neurotrophic factor, providing neuroprotection and slowing the progression of neurodegenerative diseases [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the NP, progenitor cells also play a critical role in senescence and degeneration. In many IVD disorder, a reduction of NP progenitor cells has been observed [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and restoring their activity may help improve disc degeneration [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Moreover, the progression of IVD disorder is accompanied by senescence of NP progenitor cells, and mitigating the senescence of NP progenitor cells may contribute to slowing disease progression [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSingle-cell RNA sequencing (scRNA-seq) is widely employed to elucidate intrinsic cellular heterogeneity and to identify novel cellular phenotypes, including in studies of the intervertebral disc (IVD) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In this study, we aimed to investigate the distinct cellular features associated with senescence and degeneration in the NP, and to evaluate the impact of \u003cem\u003ein vitro\u003c/em\u003e culture. Specifically, a particular focus was placed on the NP progenitor cells in the contexts of senescence, degeneration. Additional samples were assessed by flow cytometry, CCK-8 assays, and differentiation analyses to validate the scRNA-seq findings. This study sought to delineate the differences between senescence and degeneration, explore the effects of \u003cem\u003ein vitro\u003c/em\u003e culture on NP cells, clarify the relationship between NP progenitor cells and these processes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHuman NP tissue collection\u003c/h2\u003e \u003cp\u003eNP samples were obtained from patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) receiving open or endoscopic surgery. All the patients were informed consent. The study followed the Declaration of Helsinki and was approved by Ethics Committee. All patients received MRI examinations before surgery for evaluation of NP via the Pfirrmann grading system [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the samples obtained from surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePfirrmann Grade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003cp\u003eS4\u003c/p\u003e \u003cp\u003eS5\u003c/p\u003e \u003cp\u003eS6\u003c/p\u003e \u003cp\u003eS7\u003c/p\u003e \u003cp\u003eS8\u003c/p\u003e \u003cp\u003eS9\u003c/p\u003e \u003cp\u003eS10\u003c/p\u003e \u003cp\u003eS11\u003c/p\u003e \u003cp\u003eS12\u003c/p\u003e \u003cp\u003eS13\u003c/p\u003e \u003cp\u003eS14\u003c/p\u003e \u003cp\u003eS15\u003c/p\u003e \u003cp\u003eS16\u003c/p\u003e \u003cp\u003eS17\u003c/p\u003e \u003cp\u003eS18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e67\u003c/p\u003e \u003cp\u003e68\u003c/p\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e90\u003c/p\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003cp\u003eII\u003c/p\u003e \u003cp\u003eII\u003c/p\u003e \u003cp\u003eII\u003c/p\u003e \u003cp\u003eIII\u003c/p\u003e \u003cp\u003eIII\u003c/p\u003e \u003cp\u003eIII\u003c/p\u003e \u003cp\u003eIV\u003c/p\u003e \u003cp\u003eIV\u003c/p\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIsolation and Adherent Culture of Human NP Cells\u003c/h3\u003e\n\u003cp\u003eNP samples were collected and put in a clean culture dish, then mechanically minced into small pieces (\u0026lt;\u0026thinsp;1 mm\u003csup\u003e3\u003c/sup\u003e) and digested with 1mg/mL collagenase II (40508ES60, Yeasen Biotechnology Co., Ltd., Shanghai, China) at 37℃ for 3 hours. The primary cells were harvested using a 70 \u0026micro;m cell strainer (WHB Scientific, Shanghai, China), centrifuged at 1000 rpm for 5 minutes, and washed twice with phosphate buffered saline (PBS). The cells were resuspended in the Dulbecco\u0026rsquo;s modified eagle medium with low glucose (Biosharp Co., Ltd., Hefei, China) containing 10% fetal bovine serum (FBS) (OriCellTM, Cyagen Biosciences Co., Ltd., Guangzhou, China) and 1% penicillin-streptomycin solution (Keygen Biotech, Nanjing, China). The cells were transferred into T25 culture flasks (Corning, NY, USA) and cultured in a humidified incubator with 5% CO\u003csup\u003e2\u003c/sup\u003e at 37℃. Half of the supernatant was replaced with fresh medium on the third day. The whole supernatant was replaced every 3 days. Cells were collected using 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes. The primary cells isolated from three NP samples were passaged to obtain corresponding first-passage cells, using 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eScRNA-seq Library Construction and Sequencing\u003c/h3\u003e\n\u003cp\u003eThe libraries were prepared with Chromium Single cell 3\u0026rsquo; Reagent v3 Kits (10\u0026times; Genomics, Pleasanton, California, USA) according to the manufacturer\u0026rsquo;s protocol. Briefly, each single-cell suspension was mixed with primers, enzymes, and the gel beads containing barcode information, then loaded on a Chromium Single Cell Controller (10\u0026times; Genomics) to generate single-cell gel beads in emulsions (GEMs). Each gel bead was bonded to one single cell and then wrapped with an oil surfactant. After generating the GEMs, reverse transcription was performed using barcoded full-length cDNA followed by the disruption of emulsions using the recovery agent and cDNA clean up with DynaBeads Myone Silane Beads (Thermo Fisher Scientific, Waltham, Massachusetts, USA). cDNA was then amplified by PCR with an appropriate number of cycles and thermal conditions that depended on the recovery cells. Subsequently, the amplified cDNA was fragmented, end-repaired, A-tailed, ligated to an index adaptor, and subjected to library amplification. The cDNA library was sequenced on a NovaSeq 6000 sequencer (Illumina, San Diego, California, USA). These procedures were performed by OE Biotech (OE Biotech Inc., Shanghai, China).\u003c/p\u003e\n\u003ch3\u003eProcessing of ScRNA-seq Data\u003c/h3\u003e\n\u003cp\u003eThe libraries were prepared with Chromium Single cell 3\u0026rsquo; Reagent v3 Kits (10\u0026times; Genomics, San Francisco, CA, USA) according to the manufacturer\u0026rsquo;s protocol. The cDNA library was sequenced on a NovaSeq 6000 sequencer (Illumina, CA, USA). The Cell Ranger software (version 6.1.2, 10\u0026times; Genomics, San Francisco, CA, USA) was utilized for cellular barcode demultiplexing, read alignment to the genome and transcriptome using the STAR aligner, and read downsampling to produce normalized aggregated data across samples. This resulted in a gene-by-cell count matrix. Subsequent processing of the unique molecular identifier (UMI) count matrix was conducted using the package Seurat (version 4.2.0) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] in R (version 4.2.2). Cells with UMI or gene counts deviating beyond two standard deviations from the mean were excluded. This approach assumes a Gaussian distribution and was used to eliminate low-quality cells and multiplets. The fraction of mitochondrial gene expression was examined to assess cell quality, and cells with mitochondrial gene contributions exceeding 10% of total counts were filtered out. The GRCh38 genome reference (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cf.10xgenomics.com/supp/cell-exp/refdata-gex-GRCh38-2020-A.tar.gz\u003c/span\u003e\u003cspan address=\"https://cf.10xgenomics.com/supp/cell-exp/refdata-gex-GRCh38-2020-A.tar.gz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed for alignment. Library size normalization was performed using the NormalizeData function. Gene expression levels were normalized with the LogNormalize method, which scales the total expression for each cell by a default factor of 10,000 and applies log transformation to the data.\u003c/p\u003e\n\u003ch3\u003eIdentification of Cell Types and Key Genes\u003c/h3\u003e\n\u003cp\u003eThe batch effects in scRNA-seq data were removed using the Harmony algorithm (version 0.1.1) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The FindClusters function in Seurat was used for cell clustering based on the gene expression profiles. Uniform manifold approximation and projection (UMAP) was used for data visualization via the RunUMAP function. Each cluster was manually identified based on the existing gene markers, which was verified by analyzing the genes and pathways. scRNA-seq data analysis was conducted using the R package SingleR (version 2.0.0) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], a computational tool designed for unbiased cell type recognition. The cellular origins of the single cells and their respective cell types were identified using reference transcriptomic datasets from the Human Primary Cell Atlas (HPCA) and Blueprint.\u003c/p\u003e \u003cp\u003eThe following steps of the analysis were performed using Python (version 3.10.18). Differentially expressed genes (DEGs) were identified using the gene ranking method implemented in Scanpy (version 1.10.4) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using GSEAPy (version 1.1.8) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Regulon activity of transcription factors (TF) was evaluated using pySCENIC (version 0.12.1) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The cells most responsive to biological perturbations within the single-cell data were identified using the PertPy (version 0.11.5) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFlow Cytometry and Cell Sorting\u003c/h2\u003e \u003cp\u003eCells from three additional samples were cultured (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The adherent cultured cells were incubated with 20 \u0026micro;g/mL Hoechst 33342 (C1022, Beyotime Biotechnology, Nantong, China) in the dark at 37℃ for 30 minutes. The cells were then digested with 0.25% trypsin-EDTA (25200-072, Gibco, NY, USA) at 37℃ for 3 minutes and resuspended in a concentration of 8 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/mL. The cells were labeled with PE anti-human CD16 antibody (302008, Biolegend, CA, USA, 1:100) and APC anti-human CD26 Antibody (302709, Biolegend, San Diego, CA, USA, 1:100), then identified and sorted via flow cytometry using BD FACSAriaIII (BD Biosciences, CA, USA) following standard procedures. Macrophages and NP cells were labeled with CD16 and CD26, respectively. The sorted NP cells were further distinguished into G1 and G2/M phase cells via Hoechst 33342 staining to reflect the cell cycle. Four cell populations were obtained in each sample: G1 phase NP cells (CD26⁺/CD16⁻/Hoechst33342⁻), G2/M phase NP cells (CD26⁺/CD16⁻/Hoechst33342⁺), macrophages (CD26⁻/CD16⁺) and double negative cells (CD26⁻/CD16\u003csup\u003e\u0026minus;\u003c/sup\u003e). Three cell populations (G1 phase NP cells, G2/M phase NP cells, and macrophages) were sorted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eNP Cells Exhibit Distinct Heterogeneity in Senescence and Degeneration\u003c/h2\u003e \u003cp\u003eWe reviewed our previous clinical samples (\u003cb\u003eS10-S18\u003c/b\u003e) and found that Pfirrmann grades and H\u0026amp;E histological scores did not correlate with \u003cem\u003ep16\u003c/em\u003e level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Consistently, public sequencing data [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] also showed no linear relationship between Pfirrmann grades and p16 level in NP samples (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-C\u003c/b\u003e). To further investigate the distinct features of senescence and degeneration in NP, six samples (\u003cb\u003eS1-S6\u003c/b\u003e) from six patients were analyzed by scRNA-seq (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The samples were divided into three \u003cem\u003ep16\u003c/em\u003e groups based on expression levels: low (0.017\u0026thinsp;\u0026plusmn;\u0026thinsp;0.109), moderate (0.050\u0026thinsp;\u0026plusmn;\u0026thinsp;0.193), and high (0.057\u0026thinsp;\u0026plusmn;\u0026thinsp;0.244), as well as into three Pfirrmann groups (Grades II, III, and IV). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA, B\u003c/b\u003e). The \u003cem\u003ep16\u003c/em\u003e and Pfirrmann level reflected the process of senescence and degeneration, respectively. First, the clusters were annotated as NP cells and immune cells via automated cell typing (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Cellular composition analysis illustrated that NP cells constituted the majority of the cellular population in NP tissue, and immune cells accounted for about 13.1% of all cells, suggesting that the environment of herniated NP was not immune-privileged. Interestingly, the proportion of immune cells increased with \u003cem\u003ep16\u003c/em\u003e level but decreased with Pfirrmann level. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further determine the subtypes, the NP cells were then re-clustered and manually annotated based on the existing cell annotation markers [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The subtypes of NP cells were identified as progenitor NP cells (ProNPC, 2.7%), regulatory NP cells (RegNPC, 4.3%), effector NP cells (EffNPC, 60.2%), homeostatic NP cells (HomoNPC, 12.4%), and fibrosis NP cells (FibroNPC, 20.4%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). The composition analysis indicated that EffNPC, FibroNPC, and HomoNPC constituted the majority of NP cells. The proportion of EffNPC increased with Pfirrmann level, while that of RegNPC decreased. However, the proportion of EffNPC and RegNPC across the \u003cem\u003ep16\u003c/em\u003e level showed opposite trends (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG, H). These results indicated the different cellular compositions between senescence and degeneration processes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMarker genes of NP cells subtypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProNPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eUBE2C, TOP2A\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegNPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCHI3L1, CXCL2, NFKB1, CP, CXCL3, IL6\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffNPC\u003c/p\u003e \u003cp\u003eHomoNPC\u003c/p\u003e \u003cp\u003eFibroNPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMSMO1, HMGCS1\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eRPS29, RPS21\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCOL1A1, COL3A1, COL6A1, MMP2, FBLN1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNP Cells Exhibit Distinct Function in Senescence and Degeneration\u003c/h2\u003e \u003cp\u003eThe cell cycle was determined to evaluate the growth status of cells. ProNPC exhibited proliferative status with S/G2 phases across each subtype, and other subtypes exhibited static status with G1/M phases (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The proliferative status, indicated by S/G2 phase, increased with \u003cem\u003ep16\u003c/em\u003e level but decreased with Pfirrmann level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, C). Similarly, GO terms across the two classifications were compared. The low group exhibited sterol metabolism features, the moderate group exhibited proliferative features, and the high group exhibited immune features (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). However, the GO terms of immune were highly exhibited in Pfirrmann II group with low level. As the Pfirrmann level increasing, the Pfirrmann III and IV groups exhibited features of stress reaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Using the Augur algorithm, it was found that RegNPC showed the most pronounced perturbation effects in both senescence and degeneration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, H). RegNPC exhibited immune-related GO terms, which were upregulated during senescence but downregulated during degeneration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG, I).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eP16\u003c/b\u003e \u003cb\u003ein ProNPC is associate with degeneration\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBuilding on the above results, the following study focuses on how the features of \u003cem\u003ep16\u003c/em\u003e are altered throughout senescence and degeneration. The primary and first-passage cell samples underwent scRNA-seq and clustering (\u003cb\u003eFigure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA\u003c/b\u003e). After \u003cem\u003ein vitro\u003c/em\u003e culture, UMAP and violin plots revealed that the first-passage NP cells had higher \u003cem\u003ep16\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B, D). ProNPC, which exhibited the most pronounced perturbation during culture, displayed the highest \u003cem\u003ep16\u003c/em\u003e expression levels among all subtypes in both primary and first-passage cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u0026ndash;F). The \u003cem\u003ep16\u003c/em\u003e levels in ProNPC of primary cells were further investigated. It was found that \u003cem\u003ep16\u003c/em\u003e levels in ProNPC decreased during degeneration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), whereas no clear pattern was observed during senescence (\u003cb\u003eFigure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e\u003c/b\u003e). To explain this phenomenon, we sought to identify the related TFs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccordingly, comparison of TF expression in ProNPC among different Pfirrmann groups revealed a subset of TFs with increased expression during degeneration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Based on the AUC scores, which reflect TF regulatory activity, across the five NP cell subtypes, only \u003cem\u003eE2F1\u003c/em\u003e exhibited higher activity in ProNPC compared with the other subtypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI). The \u003cem\u003eE2F1\u003c/em\u003e level in ProNPC decreased after culture (\u003cb\u003eFigure \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e\u003c/b\u003e). KEGG pathway analysis of \u003cem\u003eE2F1\u003c/em\u003e in ProNPC revealed its role in promoting the G1-to-S phase transition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ), opposing the inhibitory function of \u003cem\u003ep16\u003c/em\u003e. These results suggest that \u003cem\u003eE2F1\u003c/em\u003e may be a potential factor underlying the decrease in \u003cem\u003ep16\u003c/em\u003e levels in ProNPC during degeneration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe Heterogeneity in the First-passage Cultured Cells\u003c/h2\u003e \u003cp\u003eAccording to the above results, cultured NP cells displayed features of senescence; however, the effects of culture on NP cells seem unlikely to be fully equivalent to those of senescence. To explore the effects of culture, the cellular heterogeneity of \u003cem\u003ein vitro\u003c/em\u003e cultured cells was evaluated. Results showed that NP cells were the major cells (89.4% to 99.1%) during the culture while immune cells almost disappeared (10.6% to 0.9%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, C). The subtype of first-passage cells was manually re-clustered while maintaining subtype annotations of primary cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, D). Interestingly, only FibroNPC and ProNPC were detected after culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE), indicating that ProNPC and FibroNPC were the major subtypes of cultured NP cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo verify the results of scRNA-seq analysis, flow cytometry was performed on another three NP samples (\u003cb\u003eFigure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB\u003c/b\u003e), which showed that the composition of the first-passage cells included NP cells and a few macrophages (0.23%-2.96%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, G). The G2/M phase cells, which were tried to identify ProNPC, had a higher proportion in the group with low senescence and degeneration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eProliferative and Stemness Capacity of Different Cell Populations from NP\u003c/h2\u003e \u003cp\u003eThe results of CCK-8 showed that the G2/M phase NP cells exhibited the highest proliferative capacity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). After the osteogenic and adipogenic differentiation induction in G1 and G2/M phase NP cells, Alizarin Red staining and Oil Red O staining revealed red calcium nodules and lipid droplets of varying sizes after osteogenic induction and adipogenic induction, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). However, the staining showed no significant difference between G1 and G2/M phase NP cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, D). The expression of osteogenic genes (\u003cem\u003eALP\u003c/em\u003e and \u003cem\u003eOC\u003c/em\u003e) and adipogenic genes (\u003cem\u003eAPP\u003c/em\u003e and \u003cem\u003eLPL\u003c/em\u003e) was significantly increased in the G1 phase NP cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, F). These results of induction indicated the differentiation potential in the cultured NP cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSenescence and degeneration, as distinct pathological processes, displayed divergent features, particularly in immune activity. In our study, increased immune activity was the most notable characteristic of senescence. During senescence, NP exhibited an accumulation of immune cells, along with a function transition from metabolism and proliferation to immune and inflammatory. RegNPC, the immune-related subtype of NP, expanded during senescence and exhibited increased immune-related functions. During degeneration, immune activity was observed to decrease. However, previous studies have generally characterized degeneration as a process accompanied by immune activity [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. We speculate that this discrepancy may be due to the relatively low survival capacity of immune cells, which leads to their loss during degeneration-induced cellular damage, thereby reducing overall immune activity.\u003c/p\u003e \u003cp\u003eThe proliferation, as reflected by the S/G2 phase, increased as a compensatory response during senescence, but reduced with degeneration-induced damage. EffNPC proportion decreased during senescence, likely due to overall metabolic downregulation in NP, whereas it increased during degeneration, possibly reflecting their high viability.\u003c/p\u003e \u003cp\u003eThe characteristics of ProNPC, the progenitor cells of the NP, changed during senescence and degeneration, as reflected by alterations in their \u003cem\u003ep16\u003c/em\u003e levels. \u003cem\u003eP16\u003c/em\u003e is a cell cycle regulatory protein and a widely recognized marker of senescence [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. ProNPC is a \u003cem\u003ep16\u003c/em\u003e-enriched subtype; even when other subtypes in primary cells exhibit low \u003cem\u003ep16\u003c/em\u003e expression, ProNPC maintains high \u003cem\u003ep16\u003c/em\u003e levels. Despite its high proliferative capacity, ProNPC exhibits high expression of a senescence-associated molecule, which is seemingly contradictory. This paradox may be explained by the active cell cycle progression in ProNPC, predominantly in S and G2 phases, where \u003cem\u003ep16\u003c/em\u003e, as a G1-to-S phase inhibitor [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], could be upregulated compensatory, resulting in its high expression in this proliferative subtype.\u003c/p\u003e \u003cp\u003eOur study showed that overall \u003cem\u003ep16\u003c/em\u003e levels in NP exhibited no clear pattern of change during degeneration. However, \u003cem\u003ep16\u003c/em\u003e levels in ProNPC declined with degeneration, a phenomenon that may be explained by \u003cem\u003eE2F1\u003c/em\u003e. \u003cem\u003eE2F1\u003c/em\u003e, a transcription factor highly active in ProNPC, also serves as a key regulator of the cell cycle [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. \u003cem\u003eE2F1\u003c/em\u003e acts in opposition to \u003cem\u003ep16\u003c/em\u003e by promoting the G1-to-S phase transition in the cell cycle [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. An antagonistic effect of \u003cem\u003eE2F1\u003c/em\u003e on \u003cem\u003ep16\u003c/em\u003e has been reported in previous studies, mainly in cell cycle regulation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. In ProNPC, \u003cem\u003eE2F1\u003c/em\u003e is upregulated during degeneration, which may antagonize \u003cem\u003ep16\u003c/em\u003e and leading to its downregulation. In addition, elevated \u003cem\u003eE2F1\u003c/em\u003e promotes cellular stress and apoptosis, further exacerbating cell damage during degeneration.\u003c/p\u003e \u003cp\u003eWith increasing passage \u003cem\u003ein vitro\u003c/em\u003e, cells inevitably undergo senescence. However, the impact of culture on NP cells is clearly not equivalent to that of senescence. On the one hand, unlike senescence, which enhances immune activity, the proportion of immune cells in NP decreased after culture, likely due to their limited proliferative capacity. On the other hand, culture appeared to establish a dynamic balance between proliferation and homeostasis in first-passage cells. ProNPC, with their proliferative potential, sustain the cell population, whereas FibroNPC contribute to homeostasis by participating in ECM organization and senescence [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These findings suggest that FibroNPC may be a source of ECM supply.\u003c/p\u003e \u003cp\u003eHowever, this study had some limitations. First, the study had a small sample size, and thus studies with larger sample sizes were needed to validate the findings. Also, some double-negative cells (CD26\u003csup\u003e\u0026minus;\u003c/sup\u003e/CD16\u003csup\u003e\u0026minus;\u003c/sup\u003e) in NP were detected via flow cytometry. These cells were unexpected since most cells were already labeled with either CD26 or CD16. This could indicate that the markers of some cells were intracellular during the staining, leading to double-negative cells. Lastly, further studies were needed to verify the outcome of scRNA-seq.\u0026nbsp;Besides, we needed to sort the subtypes more precisely via flow cytometry.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, senescence and degeneration represent distinct pathological processes. Through scRNA-seq, this study clarifies the previously conflated concepts of senescence and degeneration, and reveals the impact of \u003cem\u003ein vitro\u003c/em\u003e culture on NP cells. Moreover, it underscores that NP progenitor cells exhibit associations with degeneration through the \u003cem\u003ep16\u003c/em\u003e expression pattern.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eECM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracellular Matrix\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEPCs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEndothelial Progenitor Cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGEMs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGel Beads in Emulsions\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHPCs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHematopoietic Progenitor Cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIVD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntervertebral Disc\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eKEGG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLBP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow Back Pain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNucleus Pulposus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNPCs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeural Progenitor Cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePBS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphate Buffered Saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSASP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSenescence\u0026mdash;Associated Secretory Phenotype\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003escRNA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eseq\u003c/b\u003e\u0026mdash;Single\u0026mdash;cell RNA Sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTFs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscription Factors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnique Molecular Identifier\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the Zhongshan Hospital Fudan University Ethics Committee (B2019-178). Written informed consent was obtained from all participants.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Featured Clinical Discipline Project of Shanghai Pudong New District (Pwyts2021-03); National Natural Science Foundation of China (Grant Number: 82001471); and Natural Science Foundation of Fujian (Grant Number: 2024J01320364).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eStudy design: Nixi Xu, Zhe Wang, Lixia Jin, Zixian Chen and Xiuhui WangConducting experiments: Nixi Xu, Zhiyang Zhang, Yinglun Chen, Xinxin Liu and Zheng LiAcquiring data: Yuanwu Cao, Chang Jiang, Zengxin Jiang, Hongping Shan and Xiaoxing JiangAnalysing data: Nixi Xu, Zhiyang Zhang and Chang JiangWriting the manuscript: Nixi Xu, Zhe Wang and Chang JiangReviewing the manuscript: all authors\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe thank OE Biotech and Dr. Xiang Li for their support in bioinformatics analysis. We thank Dr. Jianming Zeng (University of Macau), and all the members of his bioinformatics team, biotrainee, for generously sharing their experience and codes.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data of single cell sequencing collected in this study are available in National Omics Data Encyclopedia (NODE) for everyone, by the URL of https://www.biosino.org/node/project/detail/OEP001692. The analysis code needs to be requested from the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMorgan T, Wu J, Ovchinikova L, Lindner R, Blogg S, Moorin R. A national intervention to reduce imaging for low back pain by general practitioners: a retrospective economic program evaluation using Medicare Benefits Schedule data. 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J Pathol. 2008;215:253\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/path.2352\u003c/span\u003e\u003cspan address=\"10.1002/path.2352\" 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":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nucleus pulposus senescence, Nucleus pulposus degeneration, Intervertebral disc disorders, Single-cell RNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-8901869/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8901869/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSenescence and degeneration contribute to intervertebral disc disorders in the nucleus pulposus (NP) but are often conflated. This study aimed to delineate the distinct characteristics of senescence and degeneration in NP, examine the effects of \u003cem\u003ein vitro\u003c/em\u003e culture on NP cells, and clarify the involvement of NP progenitor cells.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eNP samples from six patients were analyzed by single-cell RNA sequencing, with \u003cem\u003ep16\u003c/em\u003e levels and Pfirrmann grades representing senescence and degeneration, respectively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNP cells were heterogeneous, including progenitor NP cells (ProNPC), regulatory NP cells (RegNPC), effector NP cells (EffNPC), homeostatic NP cells (HomoNPC), and fibrosis NP cells (FibroNPC). Senescence increased proliferation and immune activity, whereas degeneration decreased them; RegNPC was the most perturbed subtype. \u003cem\u003eIn vitro\u003c/em\u003e culture elevated \u003cem\u003ep16\u003c/em\u003e levels, primarily in ProNPC. In primary cells, the level of \u003cem\u003ep16\u003c/em\u003e in ProNPC decreased with degeneration, which was mainly mediated by \u003cem\u003eE2F1\u003c/em\u003e, whose level increased with degeneration. After culture, the proportion of macrophages was extremely low, with only ProNPC and FibroNPC remaining.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese findings indicated that senescence and degeneration are distinct, \u003cem\u003ein vitro\u003c/em\u003e culture alters NP cell properties, and ProNPCs are closely associated with degeneration, as reflected in \u003cem\u003ep16\u003c/em\u003e expression patterns.\u003c/p\u003e","manuscriptTitle":"Senescence and degeneration of human nucleus pulposus cells from in vivo and in vitro culture: A single-cell RNA sequencing study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 08:56:32","doi":"10.21203/rs.3.rs-8901869/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T08:28:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T20:07:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314758151079161253855092960307908827385","date":"2026-04-10T13:08:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-09T09:58:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126229178623169965077330440663536821453","date":"2026-04-08T03:00:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261912374292856836424262858718357846438","date":"2026-03-30T05:18:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"253060807036234970206595825321521664904","date":"2026-03-29T11:16:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254524717048971696084448206223199343783","date":"2026-03-27T09:08:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291077967090288143736313650017658280369","date":"2026-03-26T11:00:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329753084490337517844538309432900993157","date":"2026-03-11T18:18:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323004002797145831042830034895513275736","date":"2026-03-09T20:46:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48602294483374159062688886336678465322","date":"2026-03-09T05:19:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-09T05:16:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-18T04:08:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-18T04:08:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2026-02-17T14:00:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"594afc1a-a9f8-4853-95b8-a3f8c6220818","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T05:54:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 08:56:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8901869","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8901869","identity":"rs-8901869","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}