SOX9 regulation of Hexokinase 1 controls neuroinflammatory astrocyte subtypes in neuropathic pain

SOX9 regulation of Hexokinase 1 controls neuroinflammatory astrocyte subtypes in neuropathic pain | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article SOX9 regulation of Hexokinase 1 controls neuroinflammatory astrocyte subtypes in neuropathic pain Jessica Aijia Liu, Yonglong CHEN, Yu LIAO, Zhaoming WU, Yutong WAN, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5916660/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Neuropathic pain (NeP) results from nerve damage or disease, lacking effective treatments. Astrocytes contribute to long-lasting neuroinflammation in the dorsal horn, driving NeP development. Directly targeting astrocytes is not feasible due to their roles in supporting neuronal homeostasis and pain resolution. Despite this understanding, the heterogeneity of astrocytes and the regulation of deleterious subsets emergence in pain remain less known. Through a comprehensive approach involving metabolomic, single-cell transcriptomic, epigenomic profiling and regional astrocyte-specific perturbation studies, we identified distinct astrocyte clusters under physiological and pathological pain conditions, and elucidated mechanisms by which metabolic regulation of neuroinflammatory astrocyte subsets during pain pathogenesis. We found an astrocyte specifier, Sox9, transcriptionally regulates Hexokinase1 (HK1), a critical enzyme that catalyzes the first step in glucose metabolism irreversibly, contributing to astrocytic glycolysis homeostasis. Initial nerve damage induced abnormal phosphorylation of Sox9, triggering aberrantly activation of HK1 for high-rate glycolysis in astrocytes. Moreover, the excessive lactate production from heightened glycolysis remodeled histones of gene promoters via lactylation, H3K9la, promoting transcriptional modules of genes governing pro-inflammatory and neurotoxic signaling, which induced pathogenic astrocyte properties while reducing beneficial populations, ultimately causing persistent pain state. Importantly, we demonstrate that targeted modulation of the SOX9-HK1-H3K9la axis specifically dampens deleterious astrocyte subsets, promoting long-lasting recovery of NeP. Collectively, our findings unveil a novel immunometabolic mechanism and identify multiple potential targets for effective therapeutic interventions in the treatment of NeP. Biological sciences/Neuroscience/Diseases of the nervous system/Chronic pain Biological sciences/Neuroscience/Glial biology/Astrocyte Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Neuropathic pain (NeP) is a debilitating condition caused by a lesion or disease affecting the somatosensory system, which is characterized by long-term allodynia and hyperalgesia 1 . As a prevalent chronic disease affecting around 7–10% of the global population, NeP treatment poses significant challenges due to the lack of effective therapies, the presence of refractory pain, drug tolerance and addiction 1 . Therefore, a deeper understanding of the etiology and pathogenesis of NeP is essential to develop targeted and efficient therapies. The spinal cord serves as a relay station for noxious signals, where dorsal horn neurons modulate and ‘gate’ painful signals before transmitting them to higher brain centers. Prolonged neuroinflammation is a key mechanism driving NeP development, which promotes hyperexcitability of dorsal neurons for central sensitizations and chronic pain states. Astrocytes are major glial cells in the central nervous system (CNS), performing crucial homeostatic functions to support neurons and detoxify metabolites and peripheral insults. In response to initial nerve damage or noxious stimuli, dorsal spinal astrocytes can undergo “reactive” transition, exhibiting pro-inflammatory and neurotoxic functions that sustain neuroinflammation even after the peripheral injury sites have healed, leading to pathological pain conditions 2 , 3 . Spinal astrocytes also possess beneficial effects in modulating immune responses, nerve repairing, and pain resolving/gating 3 – 5 , posing challenges for directing targeting astrocytes. Single-cell RNA sequencing (scRNA-seq) studies revealed astrocyte heterogeneity in other neurological disorders, such as Alzheimer's disease (AD) and multiple sclerosis (MS), offering new molecular insights into therapeutic development 6 , 7 . Given the distinct actions of astrocytes in neuropathic pain, an in-depth understanding of astrocyte heterogeneity under physiological and pathological pain conditions, along with the mechanisms controlling deleterious astrocyte populations for NeP development is therefore critical, and such knowledge is currently lacking. Here, through a multimodal approach involving metabolomics, single-cell transcriptomics, and epigenetic profiling, combined with functional perturbation studies in vitro and in vivo, we uncovered mechanistic insights into the heterogeneity of dorsal horn astrocytes in NeP. We have identified that the emergence of detrimental astrocyte clusters that promote neuroinflammatory states for pathological pain conditions is induced by heightened glycolysis, which is predominately driven by aberrant activation of Hexokinases 1(HK1), a critical enzyme catalyzing the first step of glycolysis irreversibly. Notably, we have found that levels of astrocytic glycolysis mediated by HK1 are intricately linked to altered transcriptional activities of Sox9, a member of the SRY-like HMG-box family crucial for glial differentiation during development 8 , 9 . Nerve injury or noxious stimuli trigger phosphorylation of Sox9 at site 181, leading to increased nuclei translocations with abnormally high transcriptional activation of HK1. Excessive lactate production resulting from high-rate glycolysis remodeled histones of key genes controlling neuroinflammatory astrocyte subtypes through lactylation, ultimately causing profound NeP induction and development. Taken together, our study identified heterogeneous responses of astrocytes during NeP pathogenesis and unraveled the molecular mechanisms that control deleterious astrocytic properties, providing novel targets for therapeutic intervention for NeP. Results ScRNA-seq analysis of dorsal spinal astrocytes in Neuropathic pain The analysis of heterogeneous immune cells, such as microglia and macrophages, in the spinal cord has provided important insights into pain pathogenesis 10 – 12 . However, little is known about astrocyte heterogeneity and its regulation during NeP development. Thus, we used a pre-clinical model to induce NeP condition by spared nerve injury (SNI) in SD rats, which produces long-lasting mechanical allodynia and thermal hyperalgesia over 21 days post-injury (dpi) 13 (Fig. 1 A,B and Extended data Fig. S1 A-S1C ). Consistently, reactive astrocytes marked by Gfap and Nfia gradually elevated in the ipsilateral side of the spinal dorsal horn (SDH), showing morphological hypertrophy with upregulated proinflammatory and neurotoxic genes that promote nociceptive signaling for NeP 14 , 15 (Fig. 1 C-E, Extended data Figure S1 D and S1E ). Despite the subtle elevation of a few anti-inflammatory effectors, such as S100a10 and Tgf-β , neuropathic pain cannot be sufficiently resolved (Fig. 1 E ) . Collectively, these results confirmed that dorsal spinal astrocytes acquire reactive phenotypes and deleterious activities during NeP pathogenesis. Subsequently, we performed Singel-Cell RNA sequencing (ScRNA-seq) in the ipsilateral side of lumbar SDH in SNI and Sham on 14 dpi, a critical time point establishing chronification of NeP with stable expression of neuroinflammatory effectors and pain syndromes (Fig. 1 F). Based on unsupervised cell clustering, we hierarchically categorized cells into nine principal cell types according to their unique marker expression, visualized by tSNE (Fig. 1 F, Extended data Figure S1 F and S1G ). The cluster frequency analysis revealed an expansion of immune cells in the SNI group, including microglia, macrophages, and astrocytes, reflecting ongoing neuroinflammation in the SDH that induces neuronal hyperexcitability and NeP pathogenesis ( Extended data Figure S1 H ). By focusing on astrocytes, we further identified several subpopulations, namely Astro1-5, indicating multiple transcriptional states of astrocytes during the chronic transition of pain stage (Fig. 1 H and Extended data Figure S1 I ). We identified astrocyte clusters 1, 2, and 5 expanded while Astro 3 and 4 reduced during pain development. Astro1 is the most expanded subpopulation during pain development, with upregulation of key effectors for pro-inflammatory and neurotoxic signaling, such as Gstm1 , C3 , and Cfb , that are highly associated with the neuroinflammatory activities in promoting pain (Fig. 1 I, Supplementary Table S1 ) 16 , 17 . Astro 2 expressed genes involved in neurodegenerative progression (e.g., Aplp, Qdpr, Edil3 , and Hapln2 ) 18 – 20 and demyelination (e.g., Ptgds and Cryab ) 18 , 21 – 24 . Additionally, it also presents as an astrocyte-like NG2 glia subpopulation, potentially exerting neuroprotective functions in response to the injury 25 . Astro 5, which represents a small population and is defined as early transiting astrocytes, showed a subtle expansion after nerve injury and enriched with reactive markers (e.g., Gfap, Apoe, Aqp4 , and Atp1b2 ) and glutamate transporters, including Slc1a2 ( Glt1 ) (Fig. 1 I, Supplementary table S1 ). Previous studies have revealed that nerve injury elicits an initial upregulation of glutamate transporters in the spinal astrocytes, followed by a sustained downregulation 2 , 3 . Astro 3 is the most dramatically reduced subtype after nerve injury, representing astrocyte properties with homeostatic or/and repairing functions. They expressed genes for mitochondrial respiration (e.g., Ndufa4l2, Atp5f1b, Cox6a1 , and Ndufb7 ), G-protein signaling (e.g., Gng11,Rgs5 , and Pth1r ) and ion channel ( Kcnj8 ) 24 . Additionally, we also found Astro 3 is highly enriched genes involved in resolving inflammatory responses (e.g., Igfbp7 ,TGF-β–dependent IGF-binding protein 7; and Ptn ) 26 and regulating astrocytes plasticity ( Gal1 and Pdgfrb) , indicating their beneficial roles in modulating injury niche 27 – 29 . Astro 4 is also a small population expressing proliferative markers Ccnd1 and Serpine2 , which could be an early responding population but reduced in SNI during the chronic phase. Taken together, these data revealed the heterogeneity of astrocytes with distinct properties in the dorsal spinal cord during the chronic phase of pain development. Importantly, we also identified detrimental subpopulations, especially Astro 1, which may drive prolonged neuroinflammatory states for central sensitization during NeP pathogenesis. Pathogenic astrocyte states are highly associated with aberrant glycolytic activation. To investigate the potential mechanisms involved in regulating heterogeneity astrocytes in pain, in particular deleterious astrocyte clusters, we performed KEGG analysis. We find a common signaling enrichment, gluconeogenesis/glycolysis, shared among neuroinflammatory astrocyte subclusters Astro 1, early activating Astro 4 and proliferating Astro 5, suggesting a metabolic remodeling or impairment in these subclusters during pain pathogenesis (Fig. 1 I). Notably, Astro 1, 4 and 5 subclusters exhibited significantly higher enrichment of glucose transporter Slc2a1 and HK1 , the first enzyme in catalyzing the irreversible conversion of glucose to glucose-6-phosphate, playing a crucial role in controlling glycolytic flux irreversibly (Fig. 2 A and B ). Other glycolytic enzymes were either differentially enriched in Astro5 ( Tpi and Pfkp ), or uniformly present across subclusters but more prominently in astro1, 4, or/and 5 ( Gapdh, Eno1 , and Pkm ). When probing for gene modules of astrocyte subclusters from the SNI and Sham, we found robust inductions of deleterious astrocyte cluster Astro1(predominate cluster), 4, and 5 in SNI with enriched HK1 and genes associated with neuroinflammatory signaling in pain (Fig. 2 C). Immunostaining confirmed elevated expression of HK1 in dorsal spinal GFAP + astrocytes(perinuclear) with hypertrophy morphology following nerve injury as compared to Sham(Fig. 2 D). Importantly, we detected increased HK1 enzyme activity of astrocytes and glycolytic metabolites by metabolomics in the SNI group compared to Sham group (Fig. 2 E and 2 F), confirming metabolic abnormality toward heightened astrocytic glycolysis. Our time-course analysis of dorsal spinal astrocytes further revealed a positive correlation between gradually elevated glycolytic genes and the activation of pro-inflammatory genes in astrocytes during NeP development from 3 to 21 dpi (Figs. 2 G). Collectively, these findings suggest that enhanced glycolytic flux, potentially driven by aberrantly activated HK1, is highly associated with deleterious astrocyte subclusters that induce neuroinflammation for NeP pathogenesis. Potentiated HK1 drives the emergence of astrocyte deleterious clusters in promoting NeP Progression To investigate the metabolic effects mediated by HK1 on astrocyte phenotypes and functions during pain development in vivo , we specifically knock down HK1 in dorsal spinal astrocytes ipsilaterally by intraspinal injection of AAV expressing small hairpin RNA (shRNA) targeting HK1 or Scramble driven by the astrocytic-specific GFAP short-promoter (AAV-gfaABC1D-mCherry) (Fig. 3 A). Given the key role of HK1 in regulating homeostatic glycolysis, an optimized AAV amount was applied to reduce HK1 to physiological levels in SNI, as compared to Sham. The successful transduction in the dorsal astrocyte population is confirmed by wide expression of mCherry in the ipsilateral side co-localized with Gfap + cells 14 days post-injection. Reduced HK1 expression ameliorated astrocyte reactivity, as shown by reduced astrocytic hypertrophic morphology and GFAP expression (Figs. 3 B and 3 C). Hexokinase activity contributes to lower glycolytic gene expression through a feedback mechanism 30 . Indeed, decreased HK1 enzyme activity upon knocking down HK1 in astrocytes resulted in a notable downregulation of glycolytic enzymes and the depletion of glycolytic metabolites, lactate (Figs. 3 D and 3 E). Importantly, inhibition of astrocytic HK1 dramatically reduced expression of pro-inflammatory/neurotoxic genes and reactive markers of astrocytes compared to scramble control (Fig. 3 F). Additionally, we detected an elevation of Tgf-β , which typically modulates neuroinflammation for pain resolution (Fig. 3 F) 31 . Importantly, HK1 knockdown significantly abolished established NeP symptoms in the ipsilateral hind paw from 14 days post-injection, with long-lasting analgesic effects (Fig. 3 G). We next asked whether ectopically increasing endogenous levels of HK1 in astrocytes could promote neuroinflammatory responses and induce neuropathic pain. To address this issue, we conducted astrocyte-specific overexpression of HK1 in the ipsilateral side of the SDH in the Sham group, in which AAV particles of Cre recombinase driven by the short GFAP promoter were co-injected with DIO- HK1 -mCherry intraspinally (Fig. 3 H). Consistently, overexpression of HK1 enhanced HK1 enzyme activities, and increased expression of downstream glycolytic genes and lactate production (Fig. 3 I-K). This aberrant activation of HK1 leads to the induction of reactive astrocyte phenotype in Sham, as evidenced by an increased GFAP population with hypertrophic morphology (Fig. 3 L). Further analysis revealed increased neuroinflammatory profiles of FACS-enriched dorsal astrocytes after HK1 overexpression (Fig. 3 M). Despite we detected elevated anti-inflammatory genes (e.g., Il-4 ) upon HK1 overexpression, these rats still developed NeP-like behaviors from 10 days post injections, with mechanical allodynia lasting over 21 dpi, indicating the presence of chronic pain features (Fig. 3 M and 3 N). These data suggest that aberrant activation of HK1 is required and sufficient to induce NeP through promoting astrocytes’ pathogenic activities. To establish the pivotal role of HK1 in regulating astrocyte subpopulations, we performed scRNA-Seq analysis of the ipsilateral SDH with genetic manipulation of HK1 expression during early chronification stages (14 dpi) in astrocytes. Consistently, the bulk analysis of transcriptome changes in dorsal astrocytes confirmed altered immunoregulatory molecules upon HK1 knockdown and overexpression, in which HK1 expression is positively correlated with signaling for cytokines, chemokines and reactivity of astrocytes (Fig. 4 A and 4 B, Supplementary Table 2 ). By combining the datasets from Sham and SNI, we consistently identified 5 subclusters of astrocytes, with Astro 1, 2 and 3 being the prominent clusters. Similarly, Astro 1 emerged progressively in SNI characterized by deleterious populations in promoting neuroinflammation for NeP, expressing a wide range of neurotoxic and pro-inflammatory genes (e.g., S100b, C3 , and Cfb ) with HK1 enrichment (Fig. 4 C-E, Supplementary Table 2 ). This cluster was also induced upon HK1 overexpression in Sham but dramatically diminished after HK1 knockdown correlating with pain resolution. Additionally, both SNI and HK1 overexpression have dramatic negative impacts on the Astro 3 population, which is defined as the homeostatic or/and beneficial subgroup. Reduced HK1 levels in the SNI group partially restored Astro 3 subcluster. Notably, differential HK1 expression had less influence on the Astro 2 subgroup, which was significantly induced by SNI and highly associated with neurodegenerative signaling, indicating that HK1 activities play specific effects on distinct astrocyte subgroups 32 . Collectively, these results revealed the important role of aberrantly high HK1 activities in driving deleterious subgroups of astrocytes that sustain neuroinflammatory responses in the dorsal horn, contributing to NeP induction and development. SOX9 transcriptionally controls HK1 activities that determine pain responses To investigate the mechanism underlying the aberrant activation of HK1 in astrocytes, we focused on astrocytic-specific genes. Through analysis of a combined scRNA-Seq dataset of different treatments with differential HK1 activities, alongside heterogeneous astrocytic subclusters, we pinpointed, a key transcriptional factor regulating astrocyte formation and differentiation during the development 8 . The link between Sox9 and glucose metabolism has been implicated in a previous study showing overexpression of glycolytic genes (e.g., HK2 or LDHA ) induced astrocyte differentiation from pluripotent stem cells, which exhibit similar functions to Sox9 in regulating astrocyte specification 32 . Sox9 could also undergo phosphorylation, in particular at site 181, leading to enhanced transactivation to regulate distinct cellular behaviors and processes 33 – 35 . We found that Sox9 exhibited relatively high enrichment in neuroinflammatory clusters Astro 1 and 5, aligning with the expression patterns of HK1 and other top enriched deleterious effectors for pain, such as C3, Mt3, Clu , and Cfb (Fig. 2 C and Fig. 5 A). Despite time course analysis identifying the progressive increase of HK1 activities during NeP induction and pathogenesis, we did not detect a significant elevation of Sox9 at protein levels (Fig. 5 B). However, we observed a gradual increase in phosphorylated Sox9 (p-Sox9) levels in the SDH from 3dpi, peaking at 7 dpi and persisting over 21 dpi, which coincided with elevated protein levels of HK1, neuroinflammatory effector C3 and NeP responses (Fig. 1 B and Fig. 5 B). Immunofluorescence showed that p-Sox9 was barely detected in astrocytes from the Sham group whereas it was dramatically induced in the dorsal spinal astrocytes after nerve injury (Fig. 5 C and 5 D). Based on this observation, we hypothesized that astrocytic Sox9 is required for the onset or basal level of HK1 expression, while p-Sox9, which exerts enhanced transcriptional activation, will lead to aberrant activation of HK1, contributing to pain induction and development. To test this hypothesis, we first conducted intraspinal delivery of AAV9-GFAP-shRNA to target Sox9 in the ipsilateral side of the SDH during pain development (Fig. 5 E). Reduced Sox9 and p-Sox9 in astrocytes resulted in decreased expressions of HK1 and GFAP, leading to diminished HK enzyme activities and reduced production of lactate from glycolysis (Fig. 5 F- 5 H). Importantly, Sox9 knockdown in dorsal spinal astrocytes attenuated established mechanical allodynia and thermal hypersensitivity in SNI (Fig. 5 I). To investigate whether p-Sox9 contributes to higher HK1 activities that cause pain pathology, we generated GFAP-AAV-GFP-Sox9 (parental form), GFAP-AAV-GFP-Sox9 S181D (constitutively phosphorylated form) and GFAP-AAV-GFP-Sox9 S181A (non-phosphorylated form) 33 (Fig. 5 J). Constitutive activation of phosphorylated Sox9(Sox9 S181D ) in Sham dramatically induced HK1 expression in the SDH, whereas Sox9 overexpression had less impact on HK1 expression and enzyme activities (Fig. 5 K- 5 N). On the other hand, non-phosphorylated Sox9 (SOX9 S181A ) was insufficient in enhancing the expression levels of HK1 (Fig. 5 K-N). Moreover, both Sox9 and Sox9 S181D could increase GFAP astrocyte populations with hypertrophy morphology, with Sox9 S181D showing much stronger effects (Fig. 5 M and 5 N). Despite both Sox9 and Sox9 S181D induced NeP-like behaviors, including mechanical allodynia and thermal hyperalgesia in Sham, only constitutive activation of p-Sox9 in the dorsal astrocytes led to severe and sustained NeP(Fig. 5 O). In contrast, Sox9 S181A and the vehicle did not affect pain sensitivity (Fig. 5 O). These data suggest the upstream role of Sox9 and its phosphorylation in regulating differential HK1 expression and activities in astrocytes, which is highly associated with NeP pathogenesis. Further delving into the molecular mechanisms underlying p-Sox9-driven high HK1 activities in astrocytes post-injury, we observed enhanced nuclear localization of Sox9 and p-Sox9 proteins, indicating enhanced transcriptional activity for its targeted genes (Fig. 6 A). Furthermore, we identified a few putative Sox9 binding sites in the promoter regions of HK1 , suggesting direct transcriptional control (Fig. 6 B). Chromatin immunoprecipitation followed by qPCR assays showed the recruitment of Sox9 to the HK1 promoter following injury, where p-Sox9 exhibited higher enrichment of binding to the promoter regions of HK1 compared to parental Sox9(Fig. 6 C). Luciferase assay further confirmed a much higher transcriptional activity of p-Sox9(Sox9 S181D ) exhibited on HK1 promoter, particularly at binding sites 1–3, compared to Sox9 and non-phosphorylated Sox9(Sox9 S181A ) (Fig. 6 D). To establish that the transcriptional control exerted by p-Sox9 on aberrantly high HK1 expression in pain development, we knocked down HK1 together with overexpressing phosphorylated or non-phosphorylated Sox9 in astrocytes in Sham (Fig. 6 E and 6 F). In the absence of aberrant HK1 activation, elevated p-Sox9 levels failed to induce neuroinflammatory astrocytes with robust C3 production and NeP-like behaviors (Fig. 6 G and 6 H). Together, these results illustrate the pivotal role of Sox9 in the direct regulation of HK1 activities. Phosphorylated Sox9, which exhibits enhanced transcriptional activity, leads to sustained high HK1 activation under pathological conditions, enhancing glycolytic pathway in astrocytes and contributing to NeP induction and pathogenesis. p-SOX9 drives pathogenic astrocyte clusters To further explore the influence of Sox9 on the emergence of detrimental astrocyte subclusters during NeP pathogenesis, we analyzed the heterogeneous astrocyte properties in response to increased Sox9 S181D in Sham and Sox9 knockdown in SNI, linking to HK1-mediated glycolytic pathway. First, we found that reduced p-Sox9 levels significantly alleviate the hypertrophic GFAP + populations in SNI and decrease the gene expressions associated with pro-inflammation and neurotoxic and astrocyte reactivity (Fig. 5 F and Fig. 7 A). We also detected a significant elevation of an anti-inflammatory gene, TGF-β. In contrast, overexpression of SOX9 S181D in Sham induced reactive astrocytes in the dorsal spinal cord along with a set of genes encoding for pathogenic activities during pain pathogenesis (Fig. 5 L and Fig. 7 B). By combining the scRNA datasets from Sham and SNI, we revealed five astrocyte subclusters similar to those reported above (Fig. 7 C). Similarly to SNI or Sham treated with HK1 overexpression (SHAM + HK1 OE), increased Sox9 S181D reduced homeostatic and inflammatory resolving astrocytes subcluster, Astro 3, while induced neuroinflammatory astrocytes subset (Astro1) with HK1 enrichment, which express genes associated with pain signaling (e.g., C3, Cfb, Clu, CxCl2 ). Notably, Sox9 activities also influenced Astro 2, defined as a neurodegenerative-associated subcluster. Increased p-Sox9 significantly expanded Astro 2 populations, indicating the border detrimental effects of p-Sox9 in promoting injury-responsive astrocytes subclusters than HK1. Conversely, Sox9 knockdown caused a major contraction of Astro 1 and the depletion of Astro 5, confirming a suspended reactivating process and formation of neuroinflammatory properties (Fig. 7 C and 7 D). Subsequent trajectory inference analysis clearly shows that the hierarchy of astrocytic phenotypes resulted from homeostatic/inflammatory resolving cluster (Astro 3, expressing Kcni8 and Cox4i2 ) to intermediate stage including transitioning Astro 4 (Proliferating) or early reactivating Astro 5 (transiently upregulated glutamate transmitter in pain), then to more terminally neuroinflammatory Astro1 or neurodegenerative/demyelinated Astro 2 (e.g., S100b, Cryab , and Aplp1 ) (Fig. 7 E and 7 F), indicating the differential pathway in forming deleterious astrocytes clusters during pain development. Maximal differences in Sox9 , glycolytic genes, and genes for pathogenic astrocyte activities in promoting nociceptive signaling were observed mostly in Astro 1 (Fig. 7 F). Collectively, these data indicated that phosphorylation of Sox9 drives the formation of detrimental astrocyte subclusters, and is important for HK1-mediated pathogenic astrocytes in pain. The catalytic activity of HK1 induced by p-Sox9 drives histone lactylation for genes controlling neuroinflammatory astrocyte properties Next, we asked how enhanced glycolysis driven by p-Sox9-HK1 promotes detrimental astrocyte properties. Histone lactylation was recently identified as an epigenetic modification that is controlled by the amount of lactate content in cells 36 . Similar to histone acetylation, histone lactylation can directly stimulate gene transcriptions and alter the cellular status and functions, such as controlling the pro- or anti-inflammatory status of macrophages/microglia 37, 38 . The increased production of lactate in detrimental astrocytes prompted us to examine whether lactylation could affect gene expression inducing astrocyte pathogenic activities under pain conditions. Indeed, western blotting analysis of acid-extracted histones showed an increase in the levels of Pan-lysine lactylation (Pan Kla) after injury, which is abolished by glycolytic inhibitor, 2-DG, delivered via intrathecal injection (Fig. 8 A). To examine specific changes in histone lactylation in astrocytes that are associated with altered glycolysis, we performed immunofluorescence co-staining of H3K18la, H3K9la and H3K14la along with GFAP 36 . All of them can be detected in spinal astrocytes homeostatically and were significantly activated in astrocytes upon injury, with C3 elevation and responsive to glycolytic inhibition (Fig. 8 B and 8 C, Extended data Figure S2 A and S2B ). Further investigation into histone lactylation revealed that HK1 or p-Sox9 activation predominantly induces H3K9la expression, with minor effects on H3K9la or H3K14la in astrocytes. Moreover, knocking down HK1 in Sox9 S181D expressed astrocytes abolished H3K9la elevation (Fig. 8 D, Extended data Figure S2 E and S2F ). These data suggest that H3K9la is the most prevalent differentially affected histone lactylation modification in the dorsal astrocytes, controlled by the p-Sox9-HK1-lactate axis. To investigate the functional link of H3K9la with detrimental astrocyte properties in promoting NeP, we performed genome-wide CUT&Tag analysis using antibodies against H3K9la to identify candidate genes regulated by H3K9la in Sham and SNI. Analysis of k-means clustering partitioned the dataset into four distinct clusters, revealing obvious enrichment of H3K9la peaks in clusters 1 and 2, which predominantly bind within 1.5 kb of transcription start sites (TSS), spanning 17.06% promoter regions (Fig. 8 E and 8 F). Gene ontology biological process (GOBP) terms and KEGG pathways of higher H3K9la binding peaks at the gene promoter showed that these genes are enriched in cytokine/chemokines and signaling pathways for NF-kB, JAK-STAT and PI3K-AKT, which are involved in regulating pro-inflammation and glial activation (Fig. 8 G and Extended data Figure S3 A ). Specifically, we found that increased H3K9la peaks at the promoters of key genes that promote astrocytes’ deleterious activities and neuroinflammatory phenotypes in SNI (Fig. 8 H and Extended data Figure S3 B ). Consistently, a quantitative chromatin immunoprecipitation (qChIP) analysis indicated that the H3K9la levels on Gfap , C3 , and Cfb promoters are significantly elevated in astrocytes from SNI and overexpressions of HK1 and Sox9 S181D rats compared with Vector control or Sham. Furthermore, H3K9la enrichment in the promoter regions can be abolished upon HK1 knockdown in astrocytes (Fig. 8 I). Collectively, these results demonstrate that p-Sox9-HK1 drives astrocytic histone acetylation, which activates key genes regulating deleterious astrocyte properties through H3K9la modifications, contributing to NeP pathology. Discussion Astrocytes are central players in a myriad of processes in the healthy and diseased CNS, ranging from metabolism to immunity and degeneration. The analysis of the heterogeneity of microglia and macrophages has provided important insights into immune responses in pain pathogenesis. Despite astrocytes have been identified as a key driver for pro-longed neuroinflammation in the dorsal spinal cord, little is known about astrocyte heterogeneity and its regulation in NeP development. Our study identified differential astrocyte subclusters under physiological and pathological pain conditions and uncovered a novel phosphorylated Sox9-HK1-H3K19la signaling axis that controls the emergence of deleterious astrocyte subsets, which promote neuroinflammatory responses, leading to pain induction and development. Identifying astrocyte subtypes with distinct functions in pain pathologies is a major step toward better therapeutic strategies, which involves targeting detrimental clusters while preserving properties in the pro-resolution and neural repair phase for treating NeP. Our work shows that nerve injury-induced two major deleterious astrocyte subclusters, Astro 1 and 2, and dampened Astro 3. Astro 3 is a predominant population in the dorsal spinal cord under normal conditions, with enriched genes for astrocyte homeostatic functions and pain-resolving immune mediators. In contrast, Astro 1 is characterized by genes for pro-inflammatory and neurotoxic signaling, highly associated with nociceptive signaling for central sensitizations. Astro 2 is defined by its neurodegenerative and demyelinating nature and may also include an astrocyte-like NG2 glia subpopulation, potentially exerting neuroprotective functions in response to traumatic injury 25 . Our further scRNA analysis highlighted glycolysis as a common GO term enriched in detrimental astrocyte cluster Astro 1, as well as in two transiting/proliferating subclusters, Astro 4 and 5. The large glycolytic capacity of the CNS is primarily attributed to astrocytes, crucial for supporting neuronal activities and metabolism under homeostatic conditions. In response to inflammatory stimuli, astrocytes could increase their rate of glycolysis to prevent ATP depletion and cell death in vitro 39 , 40 . Enhanced astrocytic glycolysis, beneficial in certain neurodegenerative disorders like Alzheimer's disease, can improve cognition by supporting neuronal survival and axon growth in the brain 41 , 42 . However, prolonged high astrocytic glycolysis is harmful in pain pathology. Notably, we found that HK1, the first catalytic enzyme in converting glucose into glucose-6-phosphate irreversibly, is enriched in Astro1 and aberrantly activated from the early stage of pain induction, persisting over chronic phases. The heightened glycolysis induced by HK1 exerts specific effects in controlling the emergence of the detrimental Astro 1 cluster, driving immunopathogenic activities in the dorsal horn and ultimately contributing to the development of NeP. The finding aligns with a recent study demonstrating PTG −/− mouse inflammatory pain model reduces glycogen accumulation in astrocytes, leading to decreased pain-related behaviors and facilitating a quicker recovery. Additionally, this model showcases a reduced glycolytic capacity as compared with the WT dorsal spinal cord network 43 . Our studies also identified a novel regulatory link between the astrocytes specifier, Sox9 and glycolysis, potentially explaining differential metabolic programs adopted by astrocytes and neurons during development and homeostasis. Sox9 belongs to a member of the SRY-like HMG-box family, which functions as a key transcriptional regulator for the specification of astrocytes, neural crest and chondrocytes during development 9 , 44 . In adults, Sox9 expression is specifically expressed in naïve astrocytes and upregulated in reactive astrocytes following brain and spinal cord injury 8 , 45 . Previously, ours and others found that Sox9 can undergo phosphorylation, leading to distinct effects on cellular behavior and activities 33 . Here, we found that Sox9 could directly regulate HK1 expressions, contributing to glycolysis in astrocytes. Intriguingly, in response to initial nerve injury, Sox9 experiences abnormal phosphorylation, resulting in enhanced nuclear translocation and transcriptional activation, which causes aberrant activation of HK1. This phosphorylated Sox9 not only contributes to the emergence of the HK1-mediated neuroinflammatory astrocyte cluster 1, but also induces Astro 2, which represents a property with neurodegenerative and demyelination nature. It is plausible that the phosphorylation of Sox9 may trigger different downstream signaling pathways depending on the cellular context, resulting in the development of distinct astrocyte subtypes. Notably, the intimate link between transcriptional regulation of Sox9 and glycolytic changes also ha ve been implicated in a few studies. For example, Sox9 -haploinsufficient mice exhibit metabolic abnormalities with impaired glucose tolerance 46 . The ectopic expression of two key glycolytic enzymes, HK2 and LDHA, has been shown to promote astrocyte differentiation from human neural stem cells via enhanced aerobic glycolysis 32 , resembling the functions of Sox9. It is interesting to note that phosphorylated Sox9 is required to regulate neural crest delamination 33 , with recent research from Bhattacharya et al indicating that delaminating neural crest cells exhibit heightened glycolytic activities to facilitate cell migration 47 , revealing a strong link between phosphorylation of Sox9 and increased cellular glycolytic activity. The interaction between Sox9 and Hexokinase mediated glycolytic activities may represent a common regulatory axis in diverse cellular contexts in health or disease. Finally, we uncovered a significant mechanism underlying altered energy metabolism and epigenetic regulation in pain pathogenesis, which through H3K9la induction at the promoter regions of neuroinflammatory-regulatory genes for inducing specific types of deleterious astrocytes in NeP. Differential levels of metabolites, such as acetyl-CoA, ATP, and lactate can serve as substrates for histone modifications that directly stimulate gene transcription from chromatin. Recently, histone lactylation has emerged as a novel epigenetic alteration mediated by cellular lactate levels 36 . A few studies have highlighted how accumulating such substrates significantly impacts immune cell functions, such as microglia and macrophages, potentially exacerbating neurodegenerative progression 37 , 38 . Despite pain status being highly associated with metabolic diseases, diabetes, excess glucose intake, and increased lactate 48 – 50 , the link and molecular understanding of such knowledge are less documented. In our study, we found that heightened glycolysis in SNI triggers increased lactate production, resulting in elevated histone lactylations, including H3K18la, H3K9la, and H3K14la modifications, in astrocytes. The p-Sox9-HK1-lactate axis mainly contributes to H3K9la inductions in dorsal spinal astrocytes, with less effects on H3K18la and H3K14la. Analysis using Cut& Tag further indicates that H3K9la is highly enriched at the promoters of key genes responsible for inducing detrimental astrocyte phenotypes and regulating pathogenic activities, thereby leading to a sustained neuroinflammatory state in NeP. Additionally, our results imply that the complexity of histone lactylation may exist in astrocytes, possibly involving other increased histone lactylation marks, such as H3K18la and H3K14la, which may implicate distinct regulators or different subtypes of astrocytes warranting further investigation. Our study offers valuable insights to aid future epigenomic studies on pain pathogenesis. In summary, we have revealed that phosphorylated Sox9 induces aberrantly high HK1 activities that affect gene expression via histone lactylation in astrocytes. This regulatory mechanism promotes detrimental astrocyte properties in the dorsal horn, thereby contributing to NeP development. These findings may guide novel therapeutic approaches for the modulation of astrocyte pathogenic activities in other neurologic disorders. Limitations of study While our research uncovers the emergence of neuroinflammatory astrocyte subtypes mediated by p-Sox9-HK1, we have also observed the development of another potentially detrimental astrocyte subset, Astro 2, during NeP progression. Further investigations are warranted to explore the functional roles of this subset, which will provide deeper insights into the mechanisms of astrocyte heterogeneity in the initiation and maintenance of NeP. Another limitation is that we found SNI-induced other forms of lactylation, specifically H3K18la and H3K14la, in astrocytes. Further research efforts may reveal previously unidentified genes or mechanisms associated with the regulation of these histone lactylations. Methods KEY RESOURCES TABLE REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies Rabbit polyclonal anti-SOX9 Merck Millipore Cat# AB5535 Rabbit polyclonal anti-SOX9 (phospho S181) Abcam Cat# ab59252 Mouse Monoclonal anti-GFAP Abcam Cat# ab10062 Rabbit Monoclonal anti-Hexokinase I (C35C4) Cell Signaling Technology Cat# CST-2024 Mouse Monoclonal anti-C3 Santa Cruz Biotechnology Cat# sc-28294 Mouse Monoclonal anti-S100 (β-Subunit) Sigma-Aldrich Cat# S2532 Rabbit Polyclonal anti-NFIA ATLAS ANTIBODIES Cat# HPA006111 Rabbit polyclonal anti-TNF alpha Abcam Cat# ab6671 Rabbit polyclonal anti-IL-1 beta Abcam Cat# ab9722 Rabbit Monoclonal anti-IL-6 (D5W4V) XP Cell Signaling Technology Cat# CST-12912 Rabbit polyclonal anti-IL-10 Abcam Cat# ab9969 Rabbit polyclonal anti-TGF beta 1 Abcam Cat# ab92486 Mouse Monoclonal anti-beta actin Sigma-Aldrich Cat# A2228 Rabbit Polyclonal anti-Histon H3 Cell Signaling Technology Cat# CST-9715 Rabbit Monoclonal anti-Lactyl Lysine PTMBIO Cat# PTM-1401RM Rabbit Monoclonal anti-L-Lactyl-Histone H3 (Lys9) PTMBIO Cat# PTM-1419RM Rabbit Polyclonal anti-L-Lactyl-Histone H3 (Lys14) PTMBIO Cat# PTM-1414 Rabbit Monoclonal anti-L-Lactyl-Histone H3 (Lys18) PTMBIO Cat# PTM-1406RM GFAP Monoclonal antibody (GA5), eFluor™ 660 ThermoFisher/Invitrogen Cat# 50-9892-82 Bacterial and virus strains Adeno-associated viruses, genus Dependoparvovirus BrainVTA Cat #N/A Biological samples Trypan Blue Solution Gibco Cat# 15250061 Ficoll-Paque (Percoll) GE Healthcare Cat# 45-001-748 RBC lysis buffer BioLegend Cat# 420301 HBSS DAPI(4’,6-Diamidino-2-Phenylindole, Dihydrochloride) Thermofisher Scientific Cat# 1306 RIPA ThermoFisher Scientific Cat# 87788 Halt™ Protease and Phosphatase Inhibitor Cocktail (100X) ThermoFisher Scientific Cat# 78440 Critical commercial assays Hexokinase Activity Assay Kit Abcam Cat# ab136957 L-lactate assay kit Sigma Cat# MAK329 Pyruvate Assay Kit Sigma Cat# MAK071 CyQUANT cell proliferation assay kit ThermoFisher Scientific Cat# C7026 Magnetic IP/Co-IP kit ThermoFisher Scientific Cat# 88804 Nuclear and Cytoplasmic Extraction Reagents ThermoFisher Cat# 78833 Pierce™ Magnetic ChIP Kit ThermoFisher Scientific Cat# 26157 Neural Tissue Dissociation Kits Miltenyi Biotec Cat# 130-092-628 Miltenyi Neural Tissue Dissociation Kit (P) ThermoFisher Scientific Cat# 14175095 RNA extraction kit ThermoFisher/Invitrogen Cat# AM1931 QuickChange Site-Directed Mutagenesis Kit Agilent Technologies Cat# 200519 Experimental models: Organisms/strains Rat: Sprague Dawley CCMR of the University of Hong Kong Cat #N/A Recombinant DNA Plasmid: rAAV-GFAP-mCherry-5'miR-30a-shRNA(scramble)-3'-miR30a-WPREs VectorBuilder Cat #N/A Plasmid: rAAV-GFAP-EGFP-5'miR-30a-shRNA(SOX9)-3'-miR30a-WPREs, AAV9 BrainVTA Cat #N/A Plasmid: rAAV-GFAP-EGFP-WPRE BrainVTA Cat #N/A Plasmid: rAAV-GFAP-SOX9(S64A, S181A)-EGFP-WPREs BrainVTA Cat #N/A Plasmid: rAAV-GFAP-SOX9(S64D, S181D)-EGFP-WPREs BrainVTA Cat #N/A Plasmid: rAAV-GFAP-mCherry-5'miR-30a-shRNA(scramble)-3'-miR30a-WPREs BrainVTA Cat #N/A Plasmid: rAAV-GFAP-mCherry-5'miR-30a-shRNA(HK1)-3'-miR30a-WPREs BrainVTA Cat #N/A Plasmid: rAAV-CMV-DIO-HK1-2A-mCherry-WPREs BrainVTA Cat #N/A Plasmid: PGL3-basic Promega Cat# E1751 Plasmid: PGL3-HK1-Binding Site 1 (promoter) This manuscript Cat #N/A Plasmid: PGL3-HK1-Binding Site 2/3 (promoter) This manuscript Cat #N/A Plasmid: PGL3-HK1-Binding Site 4/5 (promoter) This manuscript Cat #N/A Plasmid: PGL3-HK1-Mut-Binding Site 1 (promoter) This manuscript Cat #N/A Plasmid: PGL3-HK1-Mut-Binding Site 2/3 (promoter) This manuscript Cat #N/A Software and algorithms FIJI ImageJ FIJI https://fiji.sc FlowJo v10.7 BD Biosciences www.flowjo.com FileZilla v3.42.1 FileZilla https://filezilla-project.org/ bcl2fastq Illumina https://support.illumina.com/sequencing/ sequencing_software/bcl2fastq-conversion- software.html pheatmap Kolde https://cran.r-project.org/web/ packages/pheatmap/index.html ggplot2 https://cran.r-project.org/web/ packages/ggplot2/index.html Cell Ranger Software v2.1.1 (February 26, 2018) 10x Genomics https://support.10xgenomics.com/ 2018) single-cell-gene-expression/software/ downloads/2.1 R version 4.1.3 (2022-03-10) R www.r-project.org R Studio Posit Software https://posit.co/download/rstudio-desktop/ Bioconductor v3.9.0 Bioconductor www.bioconductor.org Seurat v2.3.4 51 www.satijalab.org/seurat Monocle3 alpha v2.99.3 52 www.github.com/cole-trapnell-lab/ monocle-release/tree/monocle3_alpha KEGG Pathway Database 53 www.genome.jp/kegg/pathway.html BD FACSDivaTM Software v8.0 BD Biosciences www.bdbiosciences.com GraphPad Prism v9.4.0 GraphPad Software https://www.graphpad.com/features SnapeGene SnapGene https://www.snapgene.com IGV Integrative Genomics Viewer https://igv.org/ Microsoftâ Excelâ for Microsoft 365 Microsoft Corporation www.office.com Other NovaSeq 6000 System Illumina Cat #20012850 BD FACSAriaTM III Cell Sorter BD Biosciences Cat #648282 NanoDropTM One (Thermo Scientific) Thermo-Fisher Cat #ND-ONE-W LightCycler 480 II Real-Time PCR System Roche Life Science Cat #05015243001 CLARIOstar Plus BMG LABTECH https://www.bmglabtech.com/en/ Key table for qPCR primers: GENE NAME FORWARD (5’ to 3’) REVERSE (5’ to 3’) Primers for rat samples β-actin CAACTGGGACGATATGGAGAAG GTTGGCCTTAGGGTTCAGAG Sox9 TCTACTCCACCTTCACCTACAT CTGTGTGTAGACGGGTTGTT Gfap TGGCCACCAGTAACATGCAA CAGTTGGCGGCGATAGTCAT Hk1 GAGCGGATGTGGTCAAGTT CATGGTCCCTACTGTGTCATTC Gpi CCTGGGCATCTGGTATATCAAC ATGTCACCCTGCTGGAAATAG Pfkp GGTGCGCATGGGAATATACA CCCACTTGGCTTCCACAATA Tpi1 CCTGGCATGATCAAGGACTTAG GGATAGGGCATGGTTCACTTT Aldoa TGGCGCTGTGTGCTAAA GGCTCCACAATGGGTACAA Gapdh CCCCCAATGTATCCGTTGTG TAGCCCAGGATGCCCTTTAGT Pgk1 CACAGAAGGCTGGTGGATTT CAACTTTAGCTCCTCCCAAGATAG Pgam1 CACTGCCCTTCTGGAATGAA CCCTCCAGATGCTTGACAAT Eno1 GATGGACGGCACAGAGAATAAA TCGGCAATGTGACGGTAAAG Pkm CATCCTGTGGCTGGACTATAAG TCAGCACCTTTCTCCTTCAC Ldha GACTTGGCCGAGAGCATAAT GGAAGACATCCTCCTTGATTCC Pfkbp3 CTACCTCAACTGGATAGGTGTTC AGGGCGGAAGAAGTTGTAAG Idh2 AACACCGACGAGTCCATTTC TCAAGTAGAGCGGCCATTTC Sdha CTTTCCTACCCGCTCACATAC GCCTTTCACGGTGTCATAGA Mdh2 AACCCAGTTAACTCCACCATC AGGGTTGTCACACCGAATATC IL-1β CTTCCTAAAGATGGCTGCACTA CTGACTTGGCAGAGGACAAA IL-6 GAAGTTAGAGTCACAGAAGGAGTG GTTTGCCGAGTAGACCTCATAG Tnf-α ACCTTATCTACTCCCAGGTTCT GGCTGACTTTCTCCTGGTATG Ccl2 GTCTCAGCCAGATGCAGTTAAT CTGCTGGTGATTCTCTTGTAGTT Ccl7 AACCAGATGGGACCAATTCAT CACCGACTACTGGTGATCTTTC Cxcl10 CATTCCTGCAAGTCTATCCTGT GCTCTTGATGGCCTCAGATT Il-4 GTCACCCTGTTCTGCTTTCT GACCTGGTTCAAAGTGTTGATG Tgf-β CTGAACCAAGGAGACGGAATAC GTTTGGGACTGATCCCATTGA Stat3 ACCCAGATCCAGTCTGTAGAA GTTGGTAGCGTCCATGATCTTA C3 TGGAAAGGAGGATGGACAAAG CTGGCAGCTGTACTTCATAGG S100a10 TGCTCATGGAAAGGGAGTTC CACTGGTCCAGGTCTTTCATTA Aldoc GGCTGCTACTGAGGAGTTTATC CCATCTCCACTGCCTTCATATT S100β CAGGAAGTGGTGGACAAAGT CATGGAGACGAAGGCCATAAA Il-17 AAACGCCGAGGCCAATAA GAAGTGGAACGGTTGAGGTAG Cfb CTCGGGCTCCATGAATATCTAC TAACTCGCCACCTTCTCAATC Mx1 CTCACCTCCCACATCTGTAAAT GTATGTCTGCTCCGTACTTCTG Vim GCCCTTGAAGCTGCTAACTA ATTGAGCAGGTCCTGGTATTC Aldh1l1 GCTCCATCATCTACCATCCATC TGGTGAAGCCTCCTTTCTTATC PGL3-seq CTAGCAAAATAGGCTGTCCC NA HK1_bst-1 CTGCGCTCTCCAGACCT CGCTGCAGAGGAGACTTG HK1_bst-2 GATGGAGCTGATGCCTACAC TTCCCGAGTCCGTTCTATGA HK1_bst-3 GCTGGGTTTGCTTAGCTTTAAC CTATGTTGCAGTCCTGGTCTC HK1_bst-4 CAGAGGTCTGTAGGTTGAATGG ATAGTGATGGCTGAAGGTTGG HK1_bst-5 CACACACACACGCTACCAATA GAGCTGGCCGAAGTACATTT HK1-luci-bst-1 CCCAAGCTTGCTCCTCAGTAGCCCTGGT CCGCTCGAGTTCTCCAACAGTGTGGATGG HK1-luci-bst-2/3 CCCAAGCTTGCGCTGGGTTTGCTTAGCTTTAAC CCGCTCGAGTTCCCGAGTCCGTTCTATGA HK1-luci-bst-4/5 CCCAAGCTTGCCATTGTGTGCAGTTTCTCTTC CCGCTCGAGGTTTGTTGGCTAAGGGTTGTAT HK1-luci-bst-mut-1 CTGGCGGTTGTCACCCTCCCGGGGACCGGAGCTCCGAGGTCTGGAG CCGGCCCACTTCCTCAGTCCCCGCTAGCTGCAAGTCTCCTCTGCAGC HK1-luci-bst-mut-2 TACCTCCCATCTAATCTATTAGATACCGGTCTTTATGCTCTTTCAGAAAA CTCTCATAGAACGGACTCGGGAACTCGAGCCCGGGCTAGCACGCGTAA HK1-luci-bst-mut-3 TAAGCAAACCCAGCGCAAGCTTGGCATTCCGGTACTGTTGGTAAAG GCTTTAACGCCGGTGACCTAGCCGCTCTGTGCAGTTTCTCTTCTTT EXPERIMENTAL MODEL AND SUBJECT DETAILS Rat Male adult Sprague-Dawley (SD) rats aged between 4 to 6 weeks and weighed approximately 230 grams were sourced from the Centre for Comparative Medicine Research at the University of Hong Kong. It's important to note that this institution is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. All experimental and handling protocols were conducted with the prior approval of the Faculty Committee on the Use of Live Animals in Teaching and Research (CULATR), with reference numbers 5457-20 and 5859-21. The rats were maintained in a temperature-controlled environment at 25°C with a 12-hour light and 12-hour dark cycle, housed and used following the guidance of CCMR. They are free to access the food and water. Before any procedures, all rats were randomly assigned to their respective groups and allowed to acclimate in new cages for 2 to 3 days. Establishment of nerve injury model The injury model of spared nerve injury (SNI), originally described by Decosterd and Woolf in 2000 54 , is utilized to mimic human NeP associated with peripheral nerve injury. This model can induce early (6 months) neuropathic pain-like behaviours (e.g., allodynia and hyperalgesia) 13 , 54 , which can be evaluated using standard methods (e.g., Von Frey test, Hargreaves test, and Two Temperature Preference test). In this laboratory animal model, animals were anesthetized by intraperitoneal (i.p.) injection of 75-100 mg/kg of Ketamine (100mg/ml), 10mg/kg of Xylazine (20mg/ml) prior to surgery. An incision was made in the skin on the lateral surface of the right thigh of the rat, exposing the terminal branches of the sciatic nerves—specifically, the sural, common peroneal, and tibial nerves—by dissecting the biceps femoris muscle. The sural peroneal and tibial nerves were tightly ligated with 4-0 silk at the trifurcation point, then severed distally to the knot, with the distal nerve ends trimmed approximately 3–5 mm. The sural nerve remained untouched during the surgical procedure. In the SHAM-operated rats, the sciatic nerve was not to be ligated nor cut 55 . Intraspinal virus injections Virus was delivered into SDH of rats as previously described 56 . Rats will be subjected to subcutaneous injection with Meloxicam (1mg/kg) and Buprenorphine (0.03 to 0.05 mg/kg) a day before the surgery to reduce the pain during the procedure. All surgical procedures will be performed under anaesthesia by Ketamine and Xylazine (Ketamine: Xylazine=2:1; 1.3×BW, body weight) administrated via intra-peritoneal injection. Lidocaine hydrochloride (0.58% or 1.2 of 0.5% Lidocaine hydrochloride ×BW) can be locally applied to reduce the pain. The hair on the lumber spine will be removed via depilatory cream and shavers. Iodophor and alcohol are used to scrub the skin and avoid infection. The skin will be allowed to air dry 30s. A small incision was performed on the skin to expose the T12-L1 of the spine. The muscle on the spine may be incised and few muscles will be removed to expose the spine. A midline incision was meticulously made along the left lumbar vertebrae, extending until the spinal cord was visible between the intervertebral spaces of the T12 and T13 vertebrae. To reduce trauma, no laminectomy was carried out. The dura and arachnoid will be opened using 33-gauge bevel needle. Later, KDS Legato 130 Syringe Pump (RWD) with a 10ul Hamilton microinjection syringe, equipped on the stereotaxic apparatus, is used to deliver AAV9 virus for gene knockdown or overexpression, as well as control AAV. The 33gauge blunt needle is inserted into the spine and touched the spinal cord for injection and the injection rate is 0.2ul/min. After infusion, the microinjection syringe was left in place for 5 minutes before being gently withdrawn. After injection, the muscle on the spine will be sutured with 4-0 absorbable suture. Then, 4-0 Nylon sutures is used for skin suture. Baytril (Enrofloxaim, 6.6mg/kg, intramuscular) will be administrated immediately post-surgery and then daily for 3 days. The analgesic, buprenorphine (0.05mg/kg, subcutaneous) will be delivered post-surgery every 12 hours for 3 days and then daily injection with Meloxicam (1mg/kg) up to a week. Intrathecal drug delivery Intrathecal drug delivery, commonly referred to as the "pain pump," involves a small pump that administers pain medication directly to the spinal cord, offering more efficacy compared to oral pain medications. The pump is surgically implanted beneath the abdominal skin and dispenses pain medication through a catheter to the region surrounding the spinal cord. The protocol was referred previous method 57 . In summary, all rats were initially anesthetized with 5% isoflurane, which was maintained at 2% throughout the surgical procedure. Following the shaving and sterilization of the surgical site using povidone-iodine, a skin incision approximately 3 cm in length was created over the L2-3 lumbar spinal cord region. 2-Deoxy-D-glucose (2-DG, Sigma, D8375) for inhibition of glycolysis, or IPA-3 (APExBIO, B2169) Romidepsin (FK228) (AbMole, M2007 and MOLNOVA, M11164) were gently administered into the L2–3 intervertebral space utilizing a 1 mL syringe. The quantity of administered drugs was determined based on prior references. After the injection, 4-0 Nylon sutures is used for skin suture. Baytril (Enrofloxaim, 6.6mg/kg, intramuscular) will be administrated immediately post-surgery and then daily for 3 days. The analgesic, buprenorphine (0.05mg/kg, subcutaneous) will be delivered post-surgery every 12 hours for 3 days and then daily injection with Meloxicam (1mg/kg) up to a week. Von Frey Test For behavioural experiments, blind measurements were conducted to evaluate the pain sensitivity to stimulus for all treatments. The sample size is at least five, and Sprague Dawley (SD) rats of 230g born within 4-6 weeks were used in the same behavioural experiments. To assess mechanical allodynia, rats were tested as previously described 58 . Briefly, after habitation in a quiet room, an animal containment system comprising a transparent plastic chamber (70 × 24 × 15 cm, Designage Ltd. Hong Kong) placed on a wire mesh table is used during the assessment. Each animal is placed in the chamber, allowing access to the plantar surface of the hind paw through the metal mesh floor (70 × 36.5 × 42 cm, The Sun Furniture Manufacturing Co. Hong Kong). The animals are given 30 minutes to accommodate the environment for 30 minutes before testing. Throughout the examination, plastic filaments are applied perpendicularly to the plantar surface of the hind paw with constant pressure. Testing was conducted employing a set of calibrated Semmes-Weinstein monofilaments (commonly called Von-Frey Hairs) using the Up-Down method 58 , beginning with a 4.0 g filament (RWD, Aesthesio). The 50% paw withdraw threshold (PWT) was assessed for each rat on one or both hind paws. Every filament was gently placed on the hind paw's plantar surface for 5 seconds or until a reaction like abrupt withdrawal, shaking, or limb licking occurred. Instances of rearing or regular ambulation during filament application were disregarded. Filaments were used at intervals of five minutes until thresholds were established. Each measurement was conducted twice per rat, and the average value was considered the final PWT value. Plantar Heat Test (Hargreaves) To assess heat-thermal hyperalgesia, the ipsilateral hind paw of the animal will be measured individually using a thermal stimulus apparatus (Ugo Basile, Varese, Italy). The the beam intensity was calibrated and set to a baseline latency of 8–12 s before the test. It is noted that the administration duration of stimuli is very transient (usually less than 20 secs), and therefore, no severe injury will be generated. The determination of paw withdrawal latency will involve averaging five measurements per paw. The hind paws will be evaluated alternately, ensuring a minimum 5-minute interval between successive stimuli on the same hind paw. Responses will only be considered as withdrawal if there are swift hind paw movements, with or without hind paw licking away from the stimulus. Movements related to locomotion or weight shifting will not be classified as a response, prompting a re-test for that trial. Two Temperature Preference Analysis (TTP) Two hot/cold plates from BIO-CHP-ER, obtained from RWD Limited Company, were positioned sequentially to enclose adjacent thermal surfaces at varying temperatures within a unified chamber (165 x 165 mm). The temperature of each platform was regulated within ± 0.11°C using SMART 3.0 (PanLab) software. Rat movement between the two plates was monitored via a video tracking system over a 6-minute period. Thermal preference was determined by calculating the total time spent on each plate 59 , 60 . To evaluate rats' responses to different temperatures, one plate, designated as the reference plate, was set to 30°C for hot temperature testing, while the other plate, the test plate, was adjusted to 45°C. For cold temperature assessment, the reference plate stayed at 30°C, while the test plate was set to 20°C. Rats were gently positioned in the apparatus, aligning their bodies with the separation line between the plates and their paws situated on each plate. Subsequently, rats were allowed to move freely between plates, with their movements discreetly recorded by an overhead camera. The number of transitions between plates were recorded, and the time spent on the test plate was calculated. The equipment was methodically cleaned after each rat session, and the order of the reference and test plates were shuffled between trials to prevent bias. Prior to experimental testing, rats underwent habituation to the conditions to minimize stress. This involved spending 5 minutes daily for two days on the plates at 30°C. After this familiarization period, rats were expected to spend a similar duration on each plate during a 6-minute session, ideally between 300-360 seconds. Rats deviating significantly in time spent on either plate, making only one or no transitions, were excluded. To mitigate learning effects, the reference and test plate temperatures were switched for subsequent trials. Each rat was tested twice per parameter set, with re-habituation between trials. Video analysis via an automated tracking system (Bioseb) quantified the percentage of time spent on each plate 61 . Acetone test The acetone evaporation test is referred to the published protocol 62 . It is the good method to measure the behaviour of cold allodynia triggered by evaporative cooling 63 , 64 . Simply, rats were placed on the metal mesh floor, and acetone was sprayed on the plantar surface of the left hind paw. The behavior was record and scored. (0= no response, 1= brief flick, 2= raise more than 1s, 3= biting and flicking) Protein extracts, SDS-PAGE, and Western blotting For western blotting, harvested L3-6 left dorsal spinal cord tissue was transferred into an ice-cold glass homogenizer with 0.2ml RIPA lysis buffer (Thermo Fisher Scientific, #87788), supplemented with 1X protease inhibitor (Thermo Fisher Scientific, #78440). Tissues were slowly triturated using the homogenizer on ice and rotated every 10 min during the mechanical dissociation step. The protein concentrations were determined through the application of the BCA assay. 2X loading buffer was added to the cell lysate, 95°C boiled for 8min and 30mg of protein was used for SDS-PAGE. Equal amounts of protein (30 μg) were loaded into the wells of the SDS-PAGE gel, alongside the molecular weight marker (BIO-RED, #161-0374). Run the gel for about 20mins at 100V in running buffer (25 mM Tris base, 190 mM glycine, 0.1% SDS, pH 8.3) until the protein ladder reaches the borderline of stacking and separating gel, and then adjust the voltage to 120V for 1h. After the protein marker was separated to a suitable range, the protein was transferred from the gel to the PVDF membrane in the pre-cold transfer buffer (25 mM Tris base, 190 mM glycine, 20% methanol, pH8.3) for 1.5h at 100V on ice. Before preparing the stack, the PVDF membrane was activated with methanol for 2mins and rinsed in the transfer buffer. Then, block the membrane in blocking buffer (4% milk supplemented in the 1X PBS) at room temperature for 1 hour. After twice washing with 1X TBST (1X TBS, supplemented with 1% Triton X100), incubate the membrane overnight at 4°C with primary antibody appropriately diluted in blocking buffer. Wash the membrane twice using 1X TBST, incubate the membrane with the recommended dilution of Horseradish peroxidase (HRP)-conjugated secondary antibody in blocking buffer for 1 hour at room temperature. Wash the membrane twice using 1X TBST, and then incubate with HRP chemiluminescent substrates (Bio-Rad, # 1705062) chemiluminescent substrates and acquire images in darkroom. RNA isolation, cDNA synthesis and qPCR RNA extraction kit (Thermo Fisher Scientific, AM1931) was purchased to get total RNA from GFAP-labelled sorted cells. Briefly, cells collected from FACS were centrifuge at 750g at 4°C for 5 min to get cell pellet. Resuspended cell pellet by vortexing vigorously in 100μl Lysis Solution and putted on ice for 5min. Then, 50μl of 100% ethanol was added into the lysate and vortex briefly. Load the lysate/ethanol mixture onto a Micro Filter Cartridge Assembly to pull down RNA on the filter. Then, centrifuge for 30 sec at 12, 000g. After washed by Wash Solution 1 and 2/3, apply 10μl of Elution Solution (preheated to 75°C) to elute RNA. The extracted total RNA was used to synthesize cDNA using RT Master Mix (TaKaRa, RR036). RT-qPCR was performed using the SYBR-Green qPCR Master Mix (TaKaRa, RR420) on the LightCycler 480 System. Gene expression values were normalized and are shown as a relative fold change compared to the control samples. All experiments were conducted in biological triplicates. And all RT-qPCR primers are listed in Key table for qPCR primers. Plasmid construction The plasmids constructed for luciferase assay were referred to the previous protocol 65 . Briefly, the segments of HK1 promoter region were amplified from rat genomic DNA. The HK1 promoter segments were cloned into PGL3_basic plasmid (Promega, Cat# E1751) using restriction enzymes Xho I and Hind III. For mutation of the binding sites, Site-Directed Mutagenesis Kit (Agilent Technologies, #200519) was applied to generation mutation sites. The primer sequences are listed in Key table for qPCR primers. Fluorescence-Activated Cell Sorting (FACS) for GFAP+ astrocyte isolation Animals were perfused with 0.9% Sodium chloride (Sigma, S7653), and L3-6 left dorsal spinal cord tissue was collected on ice and rapidly chopped into small pieces using a sharp scalpel. Then, transferring the tissues into 15-ml Falcon tubes with 3 ml of Trypsin-EDTA (Sigma, T4049) digestion solution and add 6ml (30U) DNase I (Roche, 10104159001, 5U/ml) and incubated for 15 to 20 min at 37°C to dissociate tissue into single-cell suspension. During this step, 200ml pipette was used to blow the suspension up and down every 5 min. Then, 70-mm cell strainer was used to filter the final cell suspension, and 5 ml of ice-cold Hanks’ balanced salt solution (HBSS) (Thermo Fisher Scientific, 24020117) was applied to wash the strainer. The suspension was collected in a 50-ml Falcon tube and centrifuged at 450g at 4°C for 5 min. Supernatant containing dead cells and debris was discarded, and pellet was resuspended in 2 ml of ice-cold HBSS and centrifuge at 750g at 4°C for 5 min to wash it once. Discard the supernatant and resuspend the pellet in 1ml 30% Percoll (GE Healthcare, 45-001-748) [100% Percoll = 9 parts Percoll + 1 part 10× HBSS, Thermo Fisher Scientific, #14185052]. Tubes were spun at 800g for 15 min at 4°C, and pellet was collected in a new 15-ml tube and resuspended in 1 ml of FACS buffer [1X PBS (Gibco, 70013032) + 0.4% BSA (Sigma, A7638) or 1X PBS, 0.5% BSA, 2mM EDTA, 20mM Glucose] to wash once. Then, the cell pellet was resuspended in 300ul of FACS buffer with 1:50 APC anti-GFAP antibody (Thermo Fisher Scientific, #50-9892-82) and incubated on ice with rotated slightly for 1h. Cells were washed in 1ml FACS buffer, pelleted at 750g for 5min and resuspended in FACS buffer containing 4′,6-diamidino-2-phenylindole (DAPI). After staining with DAPI (Sigma, D9542, 1mg/ml in sterile H 2 O, 1:1,000 with sterile ice-cold 1X PBS) on ice for 8min, washed once and resuspended in 0.5ml FACS buffer to sort target cells using the BD FACSAria TM Fusion Cell Sorter. Cells were collected into FACS tube with 0.5ml FACS buffer. The fcs files were further analyzed using FlowJo software. Cell fraction extraction L3-6 segments SDH were harvested on day 7 after SNI, with SHAM as control, and homogenized using a Dounce homogenizer in the appropriate volume of CER I (provided by Nuclear and Cytoplasmic Extraction Reagents, Thermofisher Scientific, #78833). After vortexing vigorously and incubating on ice for 10 mins, CER II was added, incubating on ice for 1 min. Then centrifuging the tube for 5 mins at maximum speed and transferring the supernatant, in which containing the cytoplasmic fraction. The insoluble fraction was further suspended by ice-cold NER and the supernatant of lysate containing the nuclear extract. The extracted protein from cytoplasm and nuclei were performed SDS-PAGE gel. Dual Luciferase Reporter Gene Assay The luciferase assay was performed by referring previously described method 66 . In brief, after harvesting the treated hiPSC-derived astrocytes, cell lysis buffer provided by the kit (Beyotime, RG027) was used to lysis cells and the supernatant for further assay. After the buffers reached to room temperature, samples were added to firefly luciferase assay reagent and measure the relative light unit (RLU) at 560nm, using CLARIOstar Plus (BMG LABTECH), located in the CPOS, HKU. Then, the addition of Renilla luciferase assay working buffer quenches the luminescence from the firefly reaction and only obtains the luminescent signal from Renilla reaction at 465nm. Finally, calculating the ratio of luminescence from the experimental reporter to luminescence from the control reporter, with Renilla luciferase as an internal reference to eliminate variations induced by differences in cell number or transfection efficiency. Targeted Metabolomics L3-6 segments SDH were harvested on day 7 after SNI, with SHAM as control, and putted in liquid nitrogen. The tissue was ground into power using the Dounce homogenizer in the liquid nitrogen to keep samples frozen. 35mg sample per treatment was submitted to HKU proteomics and metabolomics core for analysing the metabolites in the glycolysis, TCA and PPP pathway. At lease replicants per treatment were performed and error bar was calculated. Chromatin Immunoprecipitation and Quantitative Polymerase Chain Reaction (CHIP-qPCR) The previous protocol was referred to examine the protein-DNA interaction 67 . The segments of L3-6 SDH was cut into small pieces and dissociated into single cells using enzyme provided by Neural Tissue Dissociation Kits (Miltenyi Biotec, 130-092-628). Cells then was cross-linked by formaldehyde of final concentration 1%, incubating at RT for 10 mins with slightly vertexing, and quenched by glycine at RT for 5 mins. After washed twice using PBS buffer (contain protein inhibitor), cell membranes were dissolved with the membrane lysis solutions (Pierce™ Magnetic ChIP Kit, ThermoFisher Scientific, #26157) to isolate nuclear fraction. Sonication (BioruptorPico UltraSonication System, Diagenode) at 4°C for 30 s with a 30-s pulse was applied to shear genomic DNA into chromatin fragment size range from 200 to >700 bp. 10% of supernatant after centrifugation was was kept as the input and the remaining 90% was used for immunoprecipitation with 5 μg anti-SOX9 antibody (rabbit, Merck Millipore, AB5535), anti-p-Sox9 (rabbit, Abcam, ab59252) or normal rabbit IgG control overnight at 4°C. Followingly, the protein-DNA complex was isolated using 20 μL magnetic beads. The purified DNA served as the templates for the qPCR analysis using primers flanking the binding motifs on the HK1 promoter region. The ChIP- qPCR primers used are listed in Table xx. Dead cell removal and cell preparation for single-cell RNA sequencing The protocol for the sample preparation for scRNA-seq is referring the previous published article 68 . Animals were perfused using 0.9% saline, and the dorsal horn on the left of the L3-6 spinal cord was harvested in ice-cold Hanks’ balanced salt solution (HBSS) (Thermo Fisher Scientific, 14175095) on ice and chopped into small pieces using a sharp scalpel. We use the modified papain digestion protocol to achieve single-cell suspension [Miltenyi Neural Tissue Dissociation Kit (P) 130-092-628]. In details, tissue was transferred into 15-ml Falcon tubes containing 2 ml of digestion solution, and incubated at 37°C for 10 to 15 mins. During the dissection period, the 200ml pipette was used to blow the suspension up and down every 5 min. The dissected cell suspension was passed through a 70-mm cell strainer, and 5 ml of HBSS (with Ca and Mg; Thermo Fisher Scientific, 24020117) was applied to wash the strainer. The suspension was collected in a 15-ml Falcon tube and centrifuged at 450g at 4°C for 5 min. The pellet was resuspended in 1ml 30% Percoll (GE Healthcare, 45-001-748) [9 parts Percoll + 1 part 10× HBSS (Sigma-Aldrich, H4385) = 100% Pecoll; 3 parts 100% Pecoll + 7 parts 1× HBSS = 30% Pecoll], and discarded the supernatant in which containing dead cells and debris. Tubes were spun at 800g for 15 min at 4°C, and pellet was collected in a new 15-ml tube and resuspended in 0.5 ml of HBSS buffer (1× HBSS + 0.4% BSA). Red blood cells (RBCs) were lysed by incubating cells with RBC lysis buffer (BioLegend, 420301) for 15 min at room temperature; cells were washed and resuspended in HBSS buffer. All steps were performed at 4°C. After FACS and collected DAPI negative cells, cells were counted using an automated cell counter (Thermo Fisher Scientific Countess, AMQAX1000), live/dead measures were made using trypan blue (Gibco, 15250061), and samples with a viability of higher than 70% were used for downstream scRNA-seq analysis. scRNA-seq was performed using the Chromium platform (10X Genomics, CPOS, HKU) with a 3′ gene expression V3 kit and an iNePut of ~10,000 viable cells from a debris-free suspension. The steps of Library construction and QC, NGS sequencing, and primary analysis were completed in CPOS, and the files outputted from the ‘cellranger count’ and ‘multi’ pipelines were collected for further analysis. Downstream analyses, such as graph-based clustering and differential expression analysis/visualization, were performed using the R studio and the Seurat package. Single-cell RNA sequencing and quality-control filtering Single cells in each sample were encapsulated into droplet emulsions and converted to barcoded single-cell cDNA libraries using the Chromium Single Cell 3’ V2 Li- brary, Gel Bead, Chip, and Multiplex Kit (10x Genomics), following the manufacturer’s guidelines. The isolated single cells were then loaded in each channel, targeting for a total of 10,000 cells per library. Single-cell libraries were then sequenced on a NovaSeq 6000 System (Illumina). The sequenced reads were then mapped to the rat genome (NCBI Rnor6.0) using the 10x Genomics Cell Ranger (v2.1.1) pipeline to generate the filtered gene-barcode matrix containing valid cell barcodes and transcript unique molecular identifier (UMI) counts. For each gene and each cell barcode, UMIs were counted to construct digital expression matrices, which were filtered a second time using Seurat software. Genes found in fewer than three cells and cells with 7,500 or the number of detected genes was >2,500 in order to exclude possible multiple captures, a key problem in microdroplet-based tests. We further eliminated low-quality cells where more than 4% of the counts belonged to mitochondrial genes after visually examining the distribution of cells by the fraction of expressed mitochondrial genes. These QC standards were used, and 49, 571 single cells were used in the subsequent investigations. To get the normalized count, the filtered matrix was subjected to library size normalization in Seurat. Multiple scRNA-seq dataset integration and t-SNE analysis In order to compare cell kinds and proportions under the three conditions, the dataset integration methodology was based on the previously published method 69 . Several different scRNA-seq datasets were combined into an integrated, unbatched dataset using the Seurat software (v.4.1.0). In summary, as previously mentioned, 2000 features were shown to have significant cell-to-cell variance. Use of the FindIntegrationAnchors function allowed for the identification of anchors between individual datasets. By entering these anchors into the IntegrateData function, all cells' batch-corrected expression matrices were produced, enabling the integration and analysis of cells from various datasets. Cell Ranger employs Principal Components Analysis (PCA) to alter the dimensionality of the dataset from cells x genes to cells x M, where M is a user-selectable number of principle components, in order to reduce the gene expression matrix to its most significant properties. Cell Ranger passes the PCA-reduced data into t-Stochastic Neighbor Embedding (t-SNE) in order to visualize the data in two dimensions. The cells clustered together based on shared features after non-linear dimensional reduction and the projection of all cells into two-dimensional space by t-SNE; markers for each cluster that were identified were sought using Seurat's FindAllMarkers function. The expression of the canonical markers of specific cell types was used to classify and annotate the clusters based on published research. Differential expression genes (DEGs) analysis With the following parameters, we used Seurat's "FindAllMarkers" tool to find genes that express themselves differently between clusters: min.pct = 0.1, logfc.threshold = 0.25, pseudocount.use = 0.1, only.pos = T. The p-values for comparisons and the adjusted p-values, depending on Bonferroni correction, for each gene in the dataset were obtained using the non-parametric Wilcoxon rank-sum test. The log-transformed and scaled DEGs based on gene expression were shown using a heatmap. GO Biological progress (GOBP) analysis After the DEGs was identified between the treatments, the Enricher database ( https://maayanlab.cloud/Enrichr/ ) was applied to GO enrichment analysis for the biological progress. GO terms with a p value < 0.05 were significant the highly associated GO terms of biological process were shown. KEGG pathway analysis Similar to the GOBP analysis, DEGs identified in the compared treatments was applied to KEGG enrichment analysis using the KOBAS database ( http://kobas.cbi.pku.edu.cn/ ). KEGG with a p value < 0.05 were significant the highly associated pathways were shown. Pseudotime trajectory analysis Single-cell pseudotime trajectory analysis was performed with monocle3 70 ( https://cole-trapnell-lab.github.io/monocle3/docs/trajectories/ ). The developmental processes of cell differentiation were inferred using Monocle 3. These algorithms use an individual cell's asynchronous evolution within an unsupervised framework to position the cells along a trajectory matching to a biological process. This increases the temporal resolution of transcriptome dynamics of key regulatory factors. CUT&Tag analysis In this study, we employed the CUT&Tag (Cleavage Under Targets and Tagmentation) technology to map protein-DNA interactions and histone modifications in native chromatin. The protocol begins with cell preparation and fixation to preserve chromatin integrity. Specific antibodies bind to the target proteins or histone modifications, followed by the addition of a transposase adaptor complex, which performs targeted tagmentation. This process cleaves the DNA at antibody-bound sites and inserts sequencing adapters simultaneously. The resulting DNA fragments are then extracted, amplified, and purified to create a sequencing library by the PTM BIO company. The obtained sequencing results were analyzed by using the R studio and IGV. Hexokinase activity assay For measuring the activity of hexokinase, the hexokinase activity assay kit (Abcam, ab136957) has been utilized according to the manufacturer’s instructions. In short, the harvest of cultured human astrocytes or the FAC-sorted GFAP+ astrocytes from rat dorsal spinal cord for at least 1 x 10 6 cells. The cell number can be further measured by CyQUANT cell proliferation assay kit (Invitrogen, C7026). Ice-cold assay buffer was used to lysis cells and then centrifuge at 12,000 rpm for 5 mins at 4°C to remove the insoluble materials. The supernatant was transferred into new tube, keeping on ice. For measurement, the reaction buffer and cell lysis were added into the 96-well plate and incubated for 20-60 mins at RT, followed the protocol provided by the product. Finally, measuring OD 450nm for calculation and following analysis. Lactate and pyruvate accumulation measurement For the determination of lactate and pyruvate levels in the human astrocytes and sorted GFAP + astrocyte cells from rat dorsal spinal cord after different treatments both of the SNI operation and the AAV infections by intraspinal injection. L-lactate assay kit (Sigma, MAK329) was utilized according to the manufacturer’s instructions. Statistics analysis All results are expressed as mean ± SEM. For comparison between two groups, two-tailed paired t-test was used at a designed significance level of p < 0.05. For the measurements taken at different time points were compared using one-way ANOVA followed by Turkey’s multiple comparisons or two-way repeated-measures ANOVA followed by Sidak's multiple comparison. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001. Statistical analyses were performed using GraphPad Prism 9.3.0. The statistical details of each experiment can be found in the figure legends. Declarations Acknowledgments We thank the Centre for PanorOmic Sciences of The University of Hong Kong for RNA sequencing and metabolomics services, as well as the imaging Core facility of the Neuroscience department at the City University of Hong Kong. This work was supported by General research funding from Hong Kong UGC (17107822), Health and Medical Research Fund (09201846), University Start-up grant (9610588) and funding from Peter Hung Professorship in Pain Research granted to Professor Cheung Chi Wai. Author contributions J.A.L., Y.C., and M.C contributed to the conception and design of the study; Y.C., A.W., C.F., and D.Z contributed to the acquisition and analysis of data; Y.C., H.C., and Y.L. performed the bioinformatics analyses for scRNA-Seq. Z.M., and Y.C. performed the bioinformatics analyses for CUT&Tag. J.A.L., C.W.C., and S.W.provided resources and funding. J.A.L., Y.C., and M.C., analyzed and interpreted the data. 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Trapnell, C. , et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nature Biotechnology 32 , 381-386 (2014). Additional Declarations There is NO Competing Interest. Supplementary Files TableS1DEGsinAstrocytesubclustersrelatedtoFigure1.xlsx Supplementary Table S1 TableS2KEGGorGOBPanalysis.xlsx Supplementary Table S2 figS1.tif Extended data Fig. S1 FigS2.tif Extended data Fig. S2 figS3.tif Extended data Fig. S3 Cite Share Download PDF Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Kong","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Cheung","suffix":""},{"id":412178999,"identity":"e9e1fbe0-7551-4385-9f9c-d65ee3ac431c","order_by":11,"name":"Chiwai CHEUNG","email":"","orcid":"","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Chiwai","middleName":"","lastName":"CHEUNG","suffix":""}],"badges":[],"createdAt":"2025-01-28 07:00:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5916660/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5916660/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-65092-5","type":"published","date":"2025-11-21T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76673556,"identity":"de3c90b4-c552-44ac-84b9-f9a69f4b4bd3","added_by":"auto","created_at":"2025-02-19 14:00:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1318835,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003escRNA-seq analysis identified differentially expressed astrocyte subclusters in Sham and SNI.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Schematic illustrating the experimental model and design for spared nerve injury model (SNI). dpi, days post-injury.\u003c/p\u003e\n\u003cp\u003e(B) Von Frey tests for mechanical hypersensitivity at different time points. PWT, Paw Withdrawal Threshold. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison.****, p \u0026lt; 0.0001. \u0026nbsp;(SHAM, n=5; SNI, n=5). Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(C) Western blot analysis of reactive astrocyte markers (GFAP and NFIA) using L4-6 dorsal spinal cord from -1 dpi to 21 dpi. The protein levels were normalized to actin relative to -1 dpi.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(D) The representative immunofluorescence co-stained with GFAP (green) and C3 (red) at 7 dpi in the dorsal spinal cord of SHAM and SNI. DAPI was used as a nuclei marker. The white box showed the magnified view of 3D astrocyte morphology. Scale bar = 100 µm. Arrow indicates the co-localized C3 and GFAP. Right panel is the quantification of the relative intensity of GFAP and C3 in the dorsal horn. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e . **, p \u0026lt; 0.01; ****, p \u0026lt; 0.0001. (SHAM, n=9; SNI, n=9). Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(E)qPCR analysis of markers for pan-reactivated astrocyte, neurotoxic genes, pro-inflammatory genes and anti-inflammatory genes of GFAP\u003csup\u003e+\u003c/sup\u003e-labelled FAC-sorted astrocytes from dorsal spinal cord in SHAM and SNI group at 7 dpi. (SHAM, n=3; SNI, n=3).\u003c/p\u003e\n\u003cp\u003e(F) Schematic illustrating the experimental procedure for 10´ scRNA sequencing using L4-6 dorsal spinal cord from SHAM and SNI treatment at 14 dpi. Unsupervised clustering t-distributed Stochastic Neighbor Embedding \u0026nbsp;(t-SNE) plot of different cell clusters from dorsal spinal cords.\u003c/p\u003e\n\u003cp\u003e(G) Expression scatterplots of astrocyte markers \u003cem\u003e(\u003c/em\u003ee.g.,\u003cem\u003e Aldoc\u003c/em\u003e, \u003cem\u003eGja1\u003c/em\u003e, \u003cem\u003eS100b\u003c/em\u003e and \u003cem\u003eFabp7\u003c/em\u003e) in population from dorsal spinal cords.\u003c/p\u003e\n\u003cp\u003e(H) Unsupervised clustering t-SNE plot of astrocyte populations, namely Astro 1 to Astro 5. The lower panel indicates the cluster frequency of astrocyte subpopulations.\u003c/p\u003e\n\u003cp\u003e(I) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of astrocyte subclusters and violin plot showing highly enriched genes in astrocyte subclusters.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/30101ebc252a392d96c1e5d2.png"},{"id":76673544,"identity":"b8dc63e2-ca1c-4dff-8d8b-0a826962515c","added_by":"auto","created_at":"2025-02-19 14:00:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1251851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDeleterious astrocyte subsets exhibit aberrant glycolytic activation in NeP.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Schematic illustrating pathway genes for glycolysis and TCA cycle.\u003c/p\u003e\n\u003cp\u003e(B) Violin plot\u003cem\u003e \u003c/em\u003eshowing expression of key glycolytic genes and glucose transporter (\u003cem\u003eSlc2a1\u003c/em\u003e) in five astrocyte subclusters.\u003c/p\u003e\n\u003cp\u003e(C) t-SNE plots showing heterogeneous expression patterns of genes associated with detrimental astrocyte activities in pain, glucose transporter (\u003cem\u003eSlc2a1\u003c/em\u003e)\u003cem\u003e \u003c/em\u003eand glycolytic gene HK1 in astrocyte subclusters from SHAM and SNI.\u003c/p\u003e\n\u003cp\u003e(D) The representative immunofluorescence co-stained with GFAP (red) and HK1 (green) and DAPI (blue) at 7 dpi in the dorsal spinal cord of SHAM and SNI. DAPI was used as a nuclei marker. The magnified view with indicated markers showed the colocalization of GFAP and HK1. Scale bar = 30 µm. The bar chart is the quantification of the relative intensity of GFAP and HK1. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e. *, p \u0026lt; 0.05. Data are expressed as mean ± SEM. (SHAM, n=5; SNI, n=3).\u003c/p\u003e\n\u003cp\u003e(E) Quantification of HK enzyme activity in SHAM and SNI group, using GFAP\u003csup\u003e+\u003c/sup\u003e-labelled FAC-sorted astrocytes from dorsal spinal cord. A two-tailed paired t test. **, p \u0026lt; 0.01. Data are expressed as mean ± SEM. (SHAM, n=3; SNI, n=3).\u003c/p\u003e\n\u003cp\u003e(F) Metabolomics highlighted the metabolites involved in glycolysis and the TCA cycle, utilizing L4-6 dorsal spinal cord samples collected at 7 dpi from the SNI and SHAM groups.\u003c/p\u003e\n\u003cp\u003e(G)Time-course qPCR analysis of the indicated glycolytic genes and pro-inflammatory effectors from isolated dorsal spinal astrocytes in SHAM and SNI group at different time points. (SHAM, n=3; SNI, n=3).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/cf940a725d322bd54314fced.png"},{"id":76673547,"identity":"89ff00dc-8603-4ff8-89f1-1ac88991d18f","added_by":"auto","created_at":"2025-02-19 14:00:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1671107,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnhanced glycolysis driven by high HK1 activities in astrocytes promotes NeP induction and development.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Schematic showing GFAP-AAV-mCherry delivery to the ipsilateral side of the dorsal spinal cord in SNI for Scramble or HK1 knockdown.\u003c/p\u003e\n\u003cp\u003e(B) The representative immunofluorescence co-stained with Gfap (green), HK1 (purple) and mCherry (red) in the dorsal spinal cord of SNI treated with scramble and sh\u003cem\u003eHK1\u003c/em\u003e. The magnified view showed the colocalization of mCherry, Gfapand HK1. Scale bar = 30µm. Right panel is the quantification of the relative intensity of Gfap and HK1. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e.. *, p \u0026lt; 0.05. (SNI+\u003cem\u003eScr\u003c/em\u003e, n\u0026gt;=12; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=6). Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(C) Western blot analysis of HK1 and GFAP in the dorsal spinal cord from SNI treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. The protein levels were normalized to actin relative to Scr.\u003c/p\u003e\n\u003cp\u003e(D) HK enzyme activity analysis in SNI treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. A two-tailed paired \u003cem\u003et test\u003c/em\u003e. ***, p \u0026lt; 0.001. All data are mean ± SEM. (SNI+\u003cem\u003eScr\u003c/em\u003e, n=3; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(E) qPCR analysis of the indicated glycolytic and TCA genes from isolated dorsal spinal astrocytes in SNI group treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. \u0026nbsp;Right panel is the quantification of Lactate concentrations fromisolated dorsal spinal astrocytes in SNI group treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e.. *, p \u0026lt; 0.05. Data are expressed as mean ± SEM. (SNI+\u003cem\u003eScr\u003c/em\u003e, n=3; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(F) qPCR analysis of genes for astrocytic reactivity and neuroinflammation from isolated dorsal spinal astrocytes in SNI group treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. (SNI+\u003cem\u003eScr\u003c/em\u003e, n=3; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(G) Von Frey tests for mechanical hypersensitivity at different time points in SNI treated with Scramble (Scr) and sh\u003cem\u003eHK1\u003c/em\u003e. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01. Data are expressed as mean ± SEM. (SNI+\u003cem\u003eScr\u003c/em\u003e, n=3; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=4).\u003c/p\u003e\n\u003cp\u003e(H) Schematic illustrating GFAP-AAV-mCherry delivery to the ipsilateral side of the dorsal spinal cord in SHAM for Vector or \u003cem\u003eHK1\u003c/em\u003e overexpression (\u003cem\u003eHK1\u003c/em\u003e OE).\u003c/p\u003e\n\u003cp\u003e(I) Western blot analysis of HK1 and GFAP in SHAM treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. The protein levels were normalized to actin relative to Vector.\u003c/p\u003e\n\u003cp\u003e(J) qPCR analysis of the indicated glycolytic and TCA genes from isolated dorsal spinal astrocytes in SHAM group treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. (SNI+\u003cem\u003eScr\u003c/em\u003e, n=3; SNI+sh\u003cem\u003eHK1\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(K) The quantification of HK enzyme activity and lactate production in dorsal spinal astrocytes in SHAM group treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e. *, p \u0026lt; 0.05; ***, p \u0026lt; 0.001. Data are expressed as mean ± SEM. (\u003cem\u003eVector\u003c/em\u003e, n=3; \u003cem\u003eHK1 OE\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(L) The representative immunofluorescence co-stained with GFAP (green), HK1 (purple) and mCherry (red) in the dorsal spinal cord of SHAM group treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. DAPI was used as a nuclei marker. Arrows indicate triple staining. \u0026nbsp;Scale bar = 30µm. Quantification of the relative intensity of GFAP and HK1. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e. *, p \u0026lt; 0.05; ****, p \u0026lt; 0.0001. Data are expressed as mean ± SEM. (\u003cem\u003eVector\u003c/em\u003e, n=13; \u003cem\u003eHK1 OE\u003c/em\u003e, n=13).\u003c/p\u003e\n\u003cp\u003e(M) qPCR analysis of genes for astrocytic reactivity and neuroinflammation from isolated dorsal spinal astrocytes in SHAM group treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. (\u003cem\u003eVector\u003c/em\u003e, n=3; \u003cem\u003eHK1 OE\u003c/em\u003e, n=3).\u003c/p\u003e\n\u003cp\u003e(N) Von Frey tests for mechanical hypersensitivity at different time points in in SHAM group treated with Vector and \u003cem\u003eHK1\u003c/em\u003e OE. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison. ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001. Data are expressed as mean ± SEM. (\u003cem\u003eVector\u003c/em\u003e, n=5; \u003cem\u003eHK1 OE\u003c/em\u003e,, n=5).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/33406eaa964fe4e6e15a05ed.png"},{"id":76673541,"identity":"b489d424-04e9-4e01-96fe-23903bc4d2f6","added_by":"auto","created_at":"2025-02-19 14:00:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":635496,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAberrantly activated HK1 drives the emergence of astrocytic neuroinflammatory subtypes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Violin plots illustrating differential gene expression in astrocytes between the SNI group and the SNI group treated with sh\u003cem\u003eHK1\u003c/em\u003e. The right panel shows the KEGG analysis for the differentially downregulated genes (DEGs) in the SNI group treated with sh\u003cem\u003eHK1 \u003c/em\u003evs SNI.\u003c/p\u003e\n\u003cp\u003e(B) Violin plots illustrating differential gene expression in astrocytes between the SHAM group and the SHAM group treated with \u003cem\u003eHK1 \u003c/em\u003eOE. The right panel shows the KEGG analysis for the differentially upregulated genes in the SHAM treated with \u003cem\u003eHK1 \u003c/em\u003eOE vs SHAM.\u003c/p\u003e\n\u003cp\u003e(C) Unsupervised clustering t-SNE plot of astrocyte subpopulations in SHAM, SNI, SNI+sh\u003cem\u003eHK1\u003c/em\u003eand SHAM+\u003cem\u003eHK1\u003c/em\u003eOE, classified as Astro1 to 5 subclusters. The lower panel indicates the cluster frequency of astrocytes in the indicated treatments.\u003c/p\u003e\n\u003cp\u003e(D) tSNE plots showing heterogeneous expression patterns of genes associated with detrimental astrocyte activities in pain and glycolytic gene HK1 in astrocyte clusters from indicated treatments.\u003c/p\u003e\n\u003cp\u003e(E) The KEGG analysis of top enriched (up- and down-regulated) genes in Astro 1.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/f91d13a50626dcb5a069e0d8.png"},{"id":76673564,"identity":"8b2d5799-b7ea-49a5-9699-e771e6c5b7fe","added_by":"auto","created_at":"2025-02-19 14:00:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2798950,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhosphorylated Sox9 is associated with HK1 high activities, promoting NeP induction and development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) t-SNE projections and violin plots highlighting the indicated genes(\u003cem\u003eSox9\u003c/em\u003e, \u003cem\u003eHk1\u003c/em\u003e, \u003cem\u003eMt3\u003c/em\u003e, and \u003cem\u003eClu\u003c/em\u003e) \u0026nbsp;in Astro1 are presented for the combined astrocyte clusters.\u003c/p\u003e\n\u003cp\u003e(B) Western blot analysis of Sox9, p-Sox9, HK1, and C3 in the dorsal spinal cord from at different time points in SNI.\u003c/p\u003e\n\u003cp\u003e(C) The representative immunofluorescence co-stained with p-Sox9 (green) and GFAP (red) in the left panel. DAPI was used as a nuclei marker. Scale bar = 25 µm. White arrows indicate p-Sox9 in Gfap cells.\u003c/p\u003e\n\u003cp\u003e(D)Quantification of the percentage of p-Sox9 in Gfap astrocytes. A two-tailed paired t-test. *** p \u0026lt; 0.001. Two-tailed unpaired Student’s \u003cem\u003et test.\u003c/em\u003e Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(E)Schematic showing GFAP-AAV-EGFP delivery to the ipsilateral side of the dorsal spinal cord in SNI for Scramble or \u003cem\u003eSOX9 \u003c/em\u003eknockdown.\u003c/p\u003e\n\u003cp\u003e(F) Western blot analysis of Sox9, p-Sox9, Gfap and Hk1 in Sham, and SNI treated with scramble(Scr) and \u003cem\u003eSox9 \u003c/em\u003eknockdown(sh\u003cem\u003eSox9\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e(G) The representative immunofluorescence co-stained with Gfap (red), EGFP (green) and p-Sox9 (blue). Scale bar = 25 µm. White arrows indicate p-sox9 in Gfap cells. Right panel is the Quantification of the percentage of p-Sox9 in Gfap astrocytes. A two-tailed paired t-test. *** p \u0026lt; 0.001. Two-tailed unpaired Student’s \u003cem\u003et test.\u003c/em\u003e Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(H) Quantification of HK enzyme activity and lactate production in dorsal astrocytes from SNI treated with \u003cem\u003eScramble \u003c/em\u003eor \u003cem\u003eSox9 \u003c/em\u003eknockdown. A two-tailed paired \u003cem\u003et-\u003c/em\u003etest. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(I) Von Frey and Hargreaves tests for SNI treated with \u003cem\u003escramble \u003c/em\u003eor \u003cem\u003eSox9 \u003c/em\u003eknockdown. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison. *, p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001. (SNI+Scr, n=5; SNI+sh\u003cem\u003eSox9\u003c/em\u003e, n=4).\u003c/p\u003e\n\u003cp\u003e(J) Schematic showing GFAP-AAV-EGFP delivery to the ipsilateral side of the dorsal spinal for overexpression of Sox9, non-phosphorylated mutants (Sox9\u003csup\u003eS181A\u003c/sup\u003e) and phosphorylated mutants (Sox9\u003csup\u003eS181D\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003e(K) Western blot analysis of Sox9, p-Sox9, Gfap and HK1 in the indicated treatments.\u003c/p\u003e\n\u003cp\u003e(L) The representative immunofluorescence co-stained with EGFP (green), p-Sox9 (grey) and Gfap (red) in SHAM treated with \u003cem\u003eVector\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181A\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eand \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e. DAPI was used as a nuclei marker. The white box showed the magnified view. Scale bar = 50 µm. White arrows indicate p-Sox9 in EGFP; Gfap expressing cells.\u003c/p\u003e\n\u003cp\u003e(M) The representative immunofluorescence co-stained with EGFP (green), HK1 (gray) and Gfap (red) in SHAM treated with \u003cem\u003eVector\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181A\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eand \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e. DAPI was used as a nuclei marker. The white box showed the magnified view with 3D analysis showing co-colonizations of three markers. Scale bar = 50 µm. The bar chart is the quantification of the relative intensity of HK1 and Gfap in the indicated treatments. One-way ANOVA; **, p\u0026lt;0.01; ***, p\u0026lt; 0.001. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(N) Quantification of HK enzyme activity of sorted spinal astrocytes from indicated treatments. A two-tailed paired \u003cem\u003et-test\u003c/em\u003e. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(O) Von Frey and Hargreaves tests in SHAM treated with \u003cem\u003eVector\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181A\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eand \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, P \u0026lt; 0.0001. (* for \u003cem\u003eSox9\u003c/em\u003e vs \u003cem\u003eVector\u003c/em\u003e; # for \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e vs \u003cem\u003eVector\u003c/em\u003e; + for \u003cem\u003eSOX9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e vs \u003cem\u003eSox9\u003c/em\u003e; = for \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e vs \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181A\u003c/em\u003e\u003c/sup\u003e). Data are expressed as mean ± SEM.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/4ccb7a19619b3039d07f03bf.png"},{"id":76674400,"identity":"4dd9d5fd-078c-4d74-8d6f-1851e9e2db8e","added_by":"auto","created_at":"2025-02-19 14:08:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":794092,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSOX9 transcriptionally controls HK1 expressions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Western blot analysis of cell fraction extraction for p-Sox9 and Sox9 from the dorsal spinal cord at 7 dpi in SNI and SHAM.\u003c/p\u003e\n\u003cp\u003e(B) Schematic showing predicated Sox9 binding sequence and sites in \u003cem\u003eHK1\u003c/em\u003e promoter.\u003c/p\u003e\n\u003cp\u003e(C) ChIP-qPCR analysis of SOX9 and p-SOX9 at the \u003cem\u003eHK1\u003c/em\u003e promoter in the dorsal spinal cord at 14 dpi in SNI. One-way ANOVA, *, p\u0026lt;0.05; **, p\u0026lt;0.01; ***, p\u0026lt; 0.001. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(D) Dual-luciferase reporter assay showing the transactivation activity of Sox9, Sox9\u003csup\u003eS181A \u003c/sup\u003eand Sox9\u003csup\u003eS181D\u003c/sup\u003e on \u003cem\u003eHK1\u003c/em\u003e promoter regions. One-way ANOVA; *p\u0026lt;0.05\u0026nbsp; ****p \u0026lt; 0.0001. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(E) Schematic showing experimental strategy for epistatic analysis of Sox9\u003csup\u003eS181D\u003c/sup\u003e \u0026nbsp;and HK1 in the ipsilateral side of the dorsal spinal cord in SHAM.\u003c/p\u003e\n\u003cp\u003e(F) Western blot analysis of p-Sox9, HK1 and GFAP in the indicated treatments. The protein levels were normalized to actin relative to Vector.\u003c/p\u003e\n\u003cp\u003e(G) The representative immunofluorescence co-stained of EGFP (green), mCherry (red), and C3 (grey), or GFAP (purple) in SHAM treated with Vector, Sox9\u003csup\u003eS181D\u003c/sup\u003e +Scr and Sox9\u003csup\u003eS181D \u003c/sup\u003e+sh\u003cem\u003eHK1\u003c/em\u003e. DAPI was used as a nuclei marker. The white box showed the magnified view. Scale bar = 50 or 100 µm. Right panel: Quantification of relative intensity of GFAP and C3. One-way ANOVA; *, p\u0026lt;0.05; ***, p\u0026lt; 0.001. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(H) Von Frey tests for mechanical hypersensitivity at different time points of indicated treatments. Two-way repeated-measures ANOVA followed by Sidak's multiple comparison. * p \u0026lt; 0.05; ** p \u0026lt; 0.01, *** p \u0026lt; 0.001,\u0026nbsp; **** p \u0026lt; 0.0001. (Vector n=3; Sox9\u003csup\u003eS181D\u003c/sup\u003e+Scr n=3; Sox9\u003csup\u003eS181D\u003c/sup\u003e+sh\u003cem\u003eHK1\u003c/em\u003e n=5;*Sox9\u003csup\u003eS181D\u003c/sup\u003e+Scr vs Vector; # Sox9\u003csup\u003eS181D\u003c/sup\u003e+Scr vs Sox9\u003csup\u003eS181D\u003c/sup\u003e+sh\u003cem\u003eHk1\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/a7bf923f0ff6a242e3347331.png"},{"id":76673546,"identity":"2c695232-ee17-40ae-baec-19fb0754eeae","added_by":"auto","created_at":"2025-02-19 14:00:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":493757,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhosphorylated Sox9 drives the emergence of deleterious astrocytes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Western blot and qPCR analysis of key genes for astrocyte reactivity and pro-/anti-inflammatory factors in the SNI treated with scramble or \u003cem\u003eSox9 \u003c/em\u003eknockdown (A); or SHAM treated \u003cem\u003ewith Sox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181A\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eand \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D \u003c/em\u003e\u003c/sup\u003e(B).\u003c/p\u003e\n\u003cp\u003e(C) t-SNE plot and cluster frequency analysis of astrocyte clusters in the indicated treatments. (D) Feature plot showing heterogeneous expression patterns of indicated genes in different astrocyte clusters from indicated treatments.\u003c/p\u003e\n\u003cp\u003e(E) Slingshot trajectory of astrocyte clusters 1-5.\u003c/p\u003e\n\u003cp\u003e(F) Loess regression-smoothened gene expression of the indicated gene sets in pseudotime.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/9de45589119a8c891899cb46.png"},{"id":76673569,"identity":"1fe0dddd-d745-4c13-a758-3255ebecca53","added_by":"auto","created_at":"2025-02-19 14:00:58","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2436824,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH3K9la is induced by p-Sox9-HK1 axis and regulates gene expression for neuroinflammatory astrocyte subtypes during pain development.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Western blot analysis of PAN-Kla and H3K9la in the dorsal spinal cord from SHAM and SNI treated with PBS and glucose inhibitor 2-DG.\u003c/p\u003e\n\u003cp\u003e(B) The representative immunofluorescence co-stained with GFAP (red), C3 (grey) and H3K9la (green) in the dorsal spinal cord from SHAM and SNI treated with PBS and 2-DG. The white box showed the magnified view with indicated markers. Scale bar = 100 µm. Empty arrow indicates H3K9la negative in Gfap cells. White arrow indicates H3K9la and Gfap double positive cells.\u003c/p\u003e\n\u003cp\u003e(C) Quantification of the relative fold change of H3K9la in Gfap-positive cells in the dorsal spinal cord among different treatments. One-way ANOVA. *, p \u0026lt; 0.05; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001. Data are expressed as mean ± SEM. (SHAM, n=7; SNI+Pbs, n=7; SNI+2-DG, n=7).\u003c/p\u003e\n\u003cp\u003e(D) The representative immunofluorescence co-stained with EGFP (green), mCherry (red), and H3K9la (purple) in the dorsal spinal cord from indicated treatments. The white box showed the magnified view. Scale bar=20µm. The empty arrow indicates H3K9la negative in GFP+;mCherry+cells. White arrow indicates H3K9la positive in GFP+;mCherry+cells. Right panel is the quantification of the percentage of EGFP\u003csup\u003e+\u003c/sup\u003e; mCherry\u003csup\u003e+\u003c/sup\u003e H3K9la\u003csup\u003e+\u003c/sup\u003e cells in EGFP\u003csup\u003e+\u003c/sup\u003e; mCherry\u003csup\u003e+\u003c/sup\u003e cells within the dorsal horn. One-way ANOVA. ***, p \u0026lt; 0.001; **** p \u0026lt; 0.0001. Data are expressed as mean ± SEM. (Vector, n=7; \u003cem\u003eHK1\u003c/em\u003e OE, n=7; SOX9\u003csup\u003eS181D\u003c/sup\u003e+Scr, n=7; SOX9\u003csup\u003eS181D\u003c/sup\u003e+sh\u003cem\u003eHK1\u003c/em\u003e, n=7).\u003c/p\u003e\n\u003cp\u003e(E) Consensus H3K9la ± 1.5kb flanking TSSs -bound peaks are separated into 4 clusters by k-means clustering in Sham and SNI. The signals (counts per million per 10-bp bin) of each peak are shown in the clustered heatmaps (bottom panel). The profile plots (top panel) show the average signals of each cluster.\u003c/p\u003e\n\u003cp\u003e(F) The pie chart displays the distribution of H3K9la at annotated genomic regions at 7 dpi of dorsal spinal astrocytes in SHAM and SNI.\u003c/p\u003e\n\u003cp\u003e(G) The KEGG analysis of elevated H3K9la binding peaks at DEGs in SNI vs SHAM.\u003c/p\u003e\n\u003cp\u003e(H) Genome browser tracks of CUT\u0026amp;Tag signal at the indicated target gene loci from SHAM and SNI.\u003c/p\u003e\n\u003cp\u003e(I) ChIP-qPCR analysis\u003cem\u003e \u003c/em\u003eof the indicated promoters was performed using antibodies against H3K9la in the dorsal spinal cord from indicated treatment groups\u003cem\u003e.\u003c/em\u003e A two-tailed paired \u003cem\u003et-test\u003c/em\u003e. *,p \u0026lt; 0.05;\u0026nbsp; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001;\u0026nbsp; ****, p \u0026lt; 0.0001. Data are expressed as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e(H) Bar chart showing the frequency of each type of cell in SHAM and SNI treatments.\u003c/p\u003e\n\u003cp\u003e(I) Heatmap showing the top 20 genes expressed in each type of astrocyte in all treatments.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/6e2c7b431c6483616be8dd4a.png"},{"id":96513747,"identity":"87380e5f-00bf-4b78-bb45-64235c7a7869","added_by":"auto","created_at":"2025-11-22 08:08:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13048145,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/e08d8db5-2502-4c1c-9902-fca18e696dca.pdf"},{"id":76673553,"identity":"2b5f9c95-56c9-4254-bef8-e39afd02e0c6","added_by":"auto","created_at":"2025-02-19 14:00:56","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":217257,"visible":true,"origin":"","legend":"Supplementary Table S1","description":"","filename":"TableS1DEGsinAstrocytesubclustersrelatedtoFigure1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/bfbfc4c9668c7f329da7d4e5.xlsx"},{"id":76673543,"identity":"e1e4b058-1c55-430a-b180-d09323c93653","added_by":"auto","created_at":"2025-02-19 14:00:55","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13721,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table S2\u003c/p\u003e","description":"","filename":"TableS2KEGGorGOBPanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/8fe45ef44e61385e4a4b5e75.xlsx"},{"id":76673550,"identity":"7707496a-3cfd-41c9-a38d-49c486cf944b","added_by":"auto","created_at":"2025-02-19 14:00:56","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19853084,"visible":true,"origin":"","legend":"\u003cp\u003eExtended data Fig. S1\u003c/p\u003e","description":"","filename":"figS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/eab1b880ad02c53876ebe4da.tif"},{"id":76674401,"identity":"62110b4e-2081-4d0a-a36e-65f0fb73e547","added_by":"auto","created_at":"2025-02-19 14:08:57","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":59535288,"visible":true,"origin":"","legend":"\u003cp\u003eExtended data Fig. S2\u003c/p\u003e","description":"","filename":"FigS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/a71f04ecfae557a1208a08bc.tif"},{"id":76674397,"identity":"664dc658-c3bf-4434-9704-3c88f3632a87","added_by":"auto","created_at":"2025-02-19 14:08:56","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1273676,"visible":true,"origin":"","legend":"\u003cp\u003eExtended data Fig. S3\u003c/p\u003e","description":"","filename":"figS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-5916660/v1/bb2ba463bee53a7cf03e783f.tif"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"SOX9 regulation of Hexokinase 1 controls neuroinflammatory astrocyte subtypes in neuropathic pain","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNeuropathic pain (NeP) is a debilitating condition caused by a lesion or disease affecting the somatosensory system, which is characterized by long-term allodynia and hyperalgesia\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. As a prevalent chronic disease affecting around 7\u0026ndash;10% of the global population, NeP treatment poses significant challenges due to the lack of effective therapies, the presence of refractory pain, drug tolerance and addiction\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Therefore, a deeper understanding of the etiology and pathogenesis of NeP is essential to develop targeted and efficient therapies.\u003c/p\u003e \u003cp\u003eThe spinal cord serves as a relay station for noxious signals, where dorsal horn neurons modulate and \u0026lsquo;gate\u0026rsquo; painful signals before transmitting them to higher brain centers. Prolonged neuroinflammation is a key mechanism driving NeP development, which promotes hyperexcitability of dorsal neurons for central sensitizations and chronic pain states. Astrocytes are major glial cells in the central nervous system (CNS), performing crucial homeostatic functions to support neurons and detoxify metabolites and peripheral insults. In response to initial nerve damage or noxious stimuli, dorsal spinal astrocytes can undergo \u0026ldquo;reactive\u0026rdquo; transition, exhibiting pro-inflammatory and neurotoxic functions that sustain neuroinflammation even after the peripheral injury sites have healed, leading to pathological pain conditions\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Spinal astrocytes also possess beneficial effects in modulating immune responses, nerve repairing, and pain resolving/gating \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, posing challenges for directing targeting astrocytes. Single-cell RNA sequencing (scRNA-seq) studies revealed astrocyte heterogeneity in other neurological disorders, such as Alzheimer's disease (AD) and multiple sclerosis (MS), offering new molecular insights into therapeutic development \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Given the distinct actions of astrocytes in neuropathic pain, an in-depth understanding of astrocyte heterogeneity under physiological and pathological pain conditions, along with the mechanisms controlling deleterious astrocyte populations for NeP development is therefore critical, and such knowledge is currently lacking.\u003c/p\u003e \u003cp\u003eHere, through a multimodal approach involving metabolomics, single-cell transcriptomics, and epigenetic profiling, combined with functional perturbation studies in vitro and in vivo, we uncovered mechanistic insights into the heterogeneity of dorsal horn astrocytes in NeP. We have identified that the emergence of detrimental astrocyte clusters that promote neuroinflammatory states for pathological pain conditions is induced by heightened glycolysis, which is predominately driven by aberrant activation of Hexokinases 1(HK1), a critical enzyme catalyzing the first step of glycolysis irreversibly. Notably, we have found that levels of astrocytic glycolysis mediated by HK1 are intricately linked to altered transcriptional activities of Sox9, a member of the SRY-like HMG-box family crucial for glial differentiation during development\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Nerve injury or noxious stimuli trigger phosphorylation of Sox9 at site 181, leading to increased nuclei translocations with abnormally high transcriptional activation of HK1. Excessive lactate production resulting from high-rate glycolysis remodeled histones of key genes controlling neuroinflammatory astrocyte subtypes through lactylation, ultimately causing profound NeP induction and development. Taken together, our study identified heterogeneous responses of astrocytes during NeP pathogenesis and unraveled the molecular mechanisms that control deleterious astrocytic properties, providing novel targets for therapeutic intervention for NeP.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eScRNA-seq analysis of dorsal spinal astrocytes in Neuropathic pain\u003c/h2\u003e \u003cp\u003eThe analysis of heterogeneous immune cells, such as microglia and macrophages, in the spinal cord has provided important insights into pain pathogenesis \u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. However, little is known about astrocyte heterogeneity and its regulation during NeP development. Thus, we used a pre-clinical model to induce NeP condition by spared nerve injury (SNI) in SD rats, which produces long-lasting mechanical allodynia and thermal hyperalgesia over 21 days post-injury (dpi)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA,B \u003cb\u003eand Extended data Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-S1C\u003c/b\u003e). Consistently, reactive astrocytes marked by Gfap and Nfia gradually elevated in the ipsilateral side of the spinal dorsal horn (SDH), showing morphological hypertrophy with upregulated proinflammatory and neurotoxic genes that promote nociceptive signaling for NeP\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-E, \u003cb\u003eExtended data Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD and S1E\u003c/b\u003e ). Despite the subtle elevation of a few anti-inflammatory effectors, such as \u003cem\u003eS100a10\u003c/em\u003e and \u003cem\u003eTgf-β\u003c/em\u003e, neuropathic pain cannot be sufficiently resolved (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Collectively, these results confirmed that dorsal spinal astrocytes acquire reactive phenotypes and deleterious activities during NeP pathogenesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSubsequently, we performed Singel-Cell RNA sequencing (ScRNA-seq) in the ipsilateral side of lumbar SDH in SNI and Sham on 14 dpi, a critical time point establishing chronification of NeP with stable expression of neuroinflammatory effectors and pain syndromes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Based on unsupervised cell clustering, we hierarchically categorized cells into nine principal cell types according to their unique marker expression, visualized by tSNE (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, \u003cb\u003eExtended data Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eF and S1G\u003c/b\u003e). The cluster frequency analysis revealed an expansion of immune cells in the SNI group, including microglia, macrophages, and astrocytes, reflecting ongoing neuroinflammation in the SDH that induces neuronal hyperexcitability and NeP pathogenesis (\u003cb\u003eExtended data Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eH\u003c/b\u003e). By focusing on astrocytes, we further identified several subpopulations, namely Astro1-5, indicating multiple transcriptional states of astrocytes during the chronic transition of pain stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH \u003cb\u003eand Extended data Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eI\u003c/b\u003e). We identified astrocyte clusters 1, 2, and 5 expanded while Astro 3 and 4 reduced during pain development. Astro1 is the most expanded subpopulation during pain development, with upregulation of key effectors for pro-inflammatory and neurotoxic signaling, such as \u003cem\u003eGstm1\u003c/em\u003e, \u003cem\u003eC3\u003c/em\u003e, and \u003cem\u003eCfb\u003c/em\u003e, that are highly associated with the neuroinflammatory activities in promoting pain (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI, \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Astro 2 expressed genes involved in neurodegenerative progression (e.g., \u003cem\u003eAplp, Qdpr, Edil3\u003c/em\u003e, and \u003cem\u003eHapln2\u003c/em\u003e)\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and demyelination (e.g., \u003cem\u003ePtgds\u003c/em\u003e and\u003cem\u003eCryab\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Additionally, it also presents as an astrocyte-like NG2 glia subpopulation, potentially exerting neuroprotective functions in response to the injury\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Astro 5, which represents a small population and is defined as early transiting astrocytes, showed a subtle expansion after nerve injury and enriched with reactive markers (e.g., \u003cem\u003eGfap, Apoe, Aqp4\u003c/em\u003e, and \u003cem\u003eAtp1b2\u003c/em\u003e) and glutamate transporters, including \u003cem\u003eSlc1a2\u003c/em\u003e (\u003cem\u003eGlt1\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI, \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Previous studies have revealed that nerve injury elicits an initial upregulation of glutamate transporters in the spinal astrocytes, followed by a sustained downregulation\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Astro 3 is the most dramatically reduced subtype after nerve injury, representing astrocyte properties with homeostatic or/and repairing functions. They expressed genes for mitochondrial respiration (e.g., \u003cem\u003eNdufa4l2, Atp5f1b, Cox6a1\u003c/em\u003e, and \u003cem\u003eNdufb7\u003c/em\u003e), G-protein signaling (e.g., \u003cem\u003eGng11,Rgs5\u003c/em\u003e, and \u003cem\u003ePth1r\u003c/em\u003e) and ion channel (\u003cem\u003eKcnj8\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Additionally, we also found Astro 3 is highly enriched genes involved in resolving inflammatory responses (e.g., \u003cem\u003eIgfbp7\u003c/em\u003e,TGF-β\u0026ndash;dependent IGF-binding protein 7; and \u003cem\u003ePtn\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and regulating astrocytes plasticity (\u003cem\u003eGal1\u003c/em\u003e and\u003cem\u003ePdgfrb)\u003c/em\u003e, indicating their beneficial roles in modulating injury niche\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Astro 4 is also a small population expressing proliferative markers \u003cem\u003eCcnd1\u003c/em\u003e and \u003cem\u003eSerpine2\u003c/em\u003e, which could be an early responding population but reduced in SNI during the chronic phase. Taken together, these data revealed the heterogeneity of astrocytes with distinct properties in the dorsal spinal cord during the chronic phase of pain development. Importantly, we also identified detrimental subpopulations, especially Astro 1, which may drive prolonged neuroinflammatory states for central sensitization during NeP pathogenesis.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePathogenic astrocyte states are highly associated with aberrant glycolytic activation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate the potential mechanisms involved in regulating heterogeneity astrocytes in pain, in particular deleterious astrocyte clusters, we performed KEGG analysis. We find a common signaling enrichment, gluconeogenesis/glycolysis, shared among neuroinflammatory astrocyte subclusters Astro 1, early activating Astro 4 and proliferating Astro 5, suggesting a metabolic remodeling or impairment in these subclusters during pain pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). Notably, Astro 1, 4 and 5 subclusters exhibited significantly higher enrichment of glucose transporter \u003cem\u003eSlc2a1\u003c/em\u003e and \u003cem\u003eHK1\u003c/em\u003e, the first enzyme in catalyzing the irreversible conversion of glucose to glucose-6-phosphate, playing a crucial role in controlling glycolytic flux irreversibly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u003cb\u003eand B\u003c/b\u003e). Other glycolytic enzymes were either differentially enriched in Astro5 (\u003cem\u003eTpi\u003c/em\u003e and \u003cem\u003ePfkp\u003c/em\u003e), or uniformly present across subclusters but more prominently in astro1, 4, or/and 5 (\u003cem\u003eGapdh, Eno1\u003c/em\u003e, \u003cem\u003eand Pkm\u003c/em\u003e). When probing for gene modules of astrocyte subclusters from the SNI and Sham, we found robust inductions of deleterious astrocyte cluster Astro1(predominate cluster), 4, and 5 in SNI with enriched \u003cem\u003eHK1\u003c/em\u003e and genes associated with neuroinflammatory signaling in pain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Immunostaining confirmed elevated expression of HK1 in dorsal spinal GFAP\u0026thinsp;+\u0026thinsp;astrocytes(perinuclear) with hypertrophy morphology following nerve injury as compared to Sham(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Importantly, we detected increased HK1 enzyme activity of astrocytes and glycolytic metabolites by metabolomics in the SNI group compared to Sham group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF), confirming metabolic abnormality toward heightened astrocytic glycolysis. Our time-course analysis of dorsal spinal astrocytes further revealed a positive correlation between gradually elevated glycolytic genes and the activation of pro-inflammatory genes in astrocytes during NeP development from 3 to 21 dpi (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). Collectively, these findings suggest that enhanced glycolytic flux, potentially driven by aberrantly activated HK1, is highly associated with deleterious astrocyte subclusters that induce neuroinflammation for NeP pathogenesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePotentiated HK1 drives the emergence of astrocyte deleterious clusters in promoting NeP Progression\u003c/h3\u003e\n\u003cp\u003eTo investigate the metabolic effects mediated by HK1 on astrocyte phenotypes and functions during pain development \u003cem\u003ein vivo\u003c/em\u003e, we specifically knock down \u003cem\u003eHK1\u003c/em\u003e in dorsal spinal astrocytes ipsilaterally by intraspinal injection of AAV expressing small hairpin RNA (shRNA) targeting \u003cem\u003eHK1\u003c/em\u003e or Scramble driven by the astrocytic-specific GFAP short-promoter (AAV-gfaABC1D-mCherry) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Given the key role of HK1 in regulating homeostatic glycolysis, an optimized AAV amount was applied to reduce HK1 to physiological levels in SNI, as compared to Sham. The successful transduction in the dorsal astrocyte population is confirmed by wide expression of mCherry in the ipsilateral side co-localized with Gfap\u0026thinsp;+\u0026thinsp;cells 14 days post-injection. Reduced HK1 expression ameliorated astrocyte reactivity, as shown by reduced astrocytic hypertrophic morphology and GFAP expression (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Hexokinase activity contributes to lower glycolytic gene expression through a feedback mechanism\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Indeed, decreased HK1 enzyme activity upon knocking down \u003cem\u003eHK1\u003c/em\u003e in astrocytes resulted in a notable downregulation of glycolytic enzymes and the depletion of glycolytic metabolites, lactate (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Importantly, inhibition of astrocytic HK1 dramatically reduced expression of pro-inflammatory/neurotoxic genes and reactive markers of astrocytes compared to scramble control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Additionally, we detected an elevation of \u003cem\u003eTgf-β\u003c/em\u003e, which typically modulates neuroinflammation for pain resolution (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Importantly, \u003cem\u003eHK1\u003c/em\u003e knockdown significantly abolished established NeP symptoms in the ipsilateral hind paw from 14 days post-injection, with long-lasting analgesic effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next asked whether ectopically increasing endogenous levels of HK1 in astrocytes could promote neuroinflammatory responses and induce neuropathic pain. To address this issue, we conducted astrocyte-specific overexpression of \u003cem\u003eHK1\u003c/em\u003e in the ipsilateral side of the SDH in the Sham group, in which AAV particles of Cre recombinase driven by the short GFAP promoter were co-injected with DIO-\u003cem\u003eHK1\u003c/em\u003e-mCherry intraspinally (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Consistently, overexpression of HK1 enhanced HK1 enzyme activities, and increased expression of downstream glycolytic genes and lactate production (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI-K). This aberrant activation of HK1 leads to the induction of reactive astrocyte phenotype in Sham, as evidenced by an increased GFAP population with hypertrophic morphology (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). Further analysis revealed increased neuroinflammatory profiles of FACS-enriched dorsal astrocytes after \u003cem\u003eHK1\u003c/em\u003e overexpression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM). Despite we detected elevated anti-inflammatory genes (e.g., \u003cem\u003eIl-4\u003c/em\u003e) upon \u003cem\u003eHK1\u003c/em\u003e overexpression, these rats still developed NeP-like behaviors from 10 days post injections, with mechanical allodynia lasting over 21 dpi, indicating the presence of chronic pain features (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). These data suggest that aberrant activation of HK1 is required and sufficient to induce NeP through promoting astrocytes\u0026rsquo; pathogenic activities.\u003c/p\u003e \u003cp\u003eTo establish the pivotal role of HK1 in regulating astrocyte subpopulations, we performed scRNA-Seq analysis of the ipsilateral SDH with genetic manipulation of HK1 expression during early chronification stages (14 dpi) in astrocytes. Consistently, the bulk analysis of transcriptome changes in dorsal astrocytes confirmed altered immunoregulatory molecules upon HK1 knockdown and overexpression, in which HK1 expression is positively correlated with signaling for cytokines, chemokines and reactivity of astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). By combining the datasets from Sham and SNI, we consistently identified 5 subclusters of astrocytes, with Astro 1, 2 and 3 being the prominent clusters. Similarly, Astro 1 emerged progressively in SNI characterized by deleterious populations in promoting neuroinflammation for NeP, expressing a wide range of neurotoxic and pro-inflammatory genes (e.g., \u003cem\u003eS100b, C3\u003c/em\u003e, and \u003cem\u003eCfb\u003c/em\u003e) with HK1 enrichment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-E, \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). This cluster was also induced upon \u003cem\u003eHK1\u003c/em\u003e overexpression in Sham but dramatically diminished after \u003cem\u003eHK1\u003c/em\u003e knockdown correlating with pain resolution. Additionally, both SNI and \u003cem\u003eHK1\u003c/em\u003e overexpression have dramatic negative impacts on the Astro 3 population, which is defined as the homeostatic or/and beneficial subgroup. Reduced HK1 levels in the SNI group partially restored Astro 3 subcluster. Notably, differential HK1 expression had less influence on the Astro 2 subgroup, which was significantly induced by SNI and highly associated with neurodegenerative signaling, indicating that HK1 activities play specific effects on distinct astrocyte subgroups\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Collectively, these results revealed the important role of aberrantly high HK1 activities in driving deleterious subgroups of astrocytes that sustain neuroinflammatory responses in the dorsal horn, contributing to NeP induction and development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eSOX9 transcriptionally controls HK1 activities that determine pain responses\u003c/h3\u003e\n\u003cp\u003eTo investigate the mechanism underlying the aberrant activation of HK1 in astrocytes, we focused on astrocytic-specific genes. Through analysis of a combined scRNA-Seq dataset of different treatments with differential HK1 activities, alongside heterogeneous astrocytic subclusters, we pinpointed, a key transcriptional factor regulating astrocyte formation and differentiation during the development \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The link between Sox9 and glucose metabolism has been implicated in a previous study showing overexpression of glycolytic genes (e.g., \u003cem\u003eHK2\u003c/em\u003e or \u003cem\u003eLDHA\u003c/em\u003e) induced astrocyte differentiation from pluripotent stem cells, which exhibit similar functions to Sox9 in regulating astrocyte specification \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Sox9 could also undergo phosphorylation, in particular at site 181, leading to enhanced transactivation to regulate distinct cellular behaviors and processes\u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. We found that \u003cem\u003eSox9\u003c/em\u003e exhibited relatively high enrichment in neuroinflammatory clusters Astro 1 and 5, aligning with the expression patterns of \u003cem\u003eHK1\u003c/em\u003e and other top enriched deleterious effectors for pain, such as \u003cem\u003eC3, Mt3, Clu\u003c/em\u003e, and \u003cem\u003eCfb\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Despite time course analysis identifying the progressive increase of HK1 activities during NeP induction and pathogenesis, we did not detect a significant elevation of Sox9 at protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). However, we observed a gradual increase in phosphorylated Sox9 (p-Sox9) levels in the SDH from 3dpi, peaking at 7 dpi and persisting over 21 dpi, which coincided with elevated protein levels of HK1, neuroinflammatory effector C3 and NeP responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Immunofluorescence showed that p-Sox9 was barely detected in astrocytes from the Sham group whereas it was dramatically induced in the dorsal spinal astrocytes after nerve injury (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Based on this observation, we hypothesized that astrocytic Sox9 is required for the onset or basal level of HK1 expression, while p-Sox9, which exerts enhanced transcriptional activation, will lead to aberrant activation of HK1, contributing to pain induction and development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo test this hypothesis, we first conducted intraspinal delivery of AAV9-GFAP-shRNA to target \u003cem\u003eSox9\u003c/em\u003e in the ipsilateral side of the SDH during pain development (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Reduced Sox9 and p-Sox9 in astrocytes resulted in decreased expressions of HK1 and GFAP, leading to diminished HK enzyme activities and reduced production of lactate from glycolysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). Importantly, \u003cem\u003eSox9\u003c/em\u003e knockdown in dorsal spinal astrocytes attenuated established mechanical allodynia and thermal hypersensitivity in SNI (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). To investigate whether p-Sox9 contributes to higher HK1 activities that cause pain pathology, we generated GFAP-AAV-GFP-Sox9 (parental form), GFAP-AAV-GFP-Sox9\u003csup\u003eS181D\u003c/sup\u003e (constitutively phosphorylated form) and GFAP-AAV-GFP-Sox9\u003csup\u003eS181A\u003c/sup\u003e (non-phosphorylated form)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ). Constitutive activation of phosphorylated Sox9(Sox9\u003csup\u003eS181D\u003c/sup\u003e) in Sham dramatically induced HK1 expression in the SDH, whereas Sox9 overexpression had less impact on HK1 expression and enzyme activities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eN). On the other hand, non-phosphorylated Sox9 (SOX9\u003csup\u003eS181A\u003c/sup\u003e) was insufficient in enhancing the expression levels of HK1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK-N). Moreover, both Sox9 and Sox9\u003csup\u003eS181D\u003c/sup\u003e could increase GFAP astrocyte populations with hypertrophy morphology, with Sox9\u003csup\u003eS181D\u003c/sup\u003e showing much stronger effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eM and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eN). Despite both Sox9 and Sox9\u003csup\u003eS181D\u003c/sup\u003e induced NeP-like behaviors, including mechanical allodynia and thermal hyperalgesia in Sham, only constitutive activation of p-Sox9 in the dorsal astrocytes led to severe and sustained NeP(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eO). In contrast, Sox9\u003csup\u003eS181A\u003c/sup\u003e and the vehicle did not affect pain sensitivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eO). These data suggest the upstream role of Sox9 and its phosphorylation in regulating differential HK1 expression and activities in astrocytes, which is highly associated with NeP pathogenesis.\u003c/p\u003e \u003cp\u003eFurther delving into the molecular mechanisms underlying p-Sox9-driven high HK1 activities in astrocytes post-injury, we observed enhanced nuclear localization of Sox9 and p-Sox9 proteins, indicating enhanced transcriptional activity for its targeted genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Furthermore, we identified a few putative Sox9 binding sites in the promoter regions of \u003cem\u003eHK1\u003c/em\u003e, suggesting direct transcriptional control (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Chromatin immunoprecipitation followed by qPCR assays showed the recruitment of Sox9 to the \u003cem\u003eHK1\u003c/em\u003e promoter following injury, where p-Sox9 exhibited higher enrichment of binding to the promoter regions of \u003cem\u003eHK1\u003c/em\u003e compared to parental Sox9(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Luciferase assay further confirmed a much higher transcriptional activity of p-Sox9(Sox9\u003csup\u003eS181D\u003c/sup\u003e) exhibited on \u003cem\u003eHK1\u003c/em\u003e promoter, particularly at binding sites 1\u0026ndash;3, compared to Sox9 and non-phosphorylated Sox9(Sox9\u003csup\u003eS181A\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). To establish that the transcriptional control exerted by p-Sox9 on aberrantly high HK1 expression in pain development, we knocked down \u003cem\u003eHK1\u003c/em\u003e together with overexpressing phosphorylated or non-phosphorylated Sox9 in astrocytes in Sham (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). In the absence of aberrant HK1 activation, elevated p-Sox9 levels failed to induce neuroinflammatory astrocytes with robust C3 production and NeP-like behaviors (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTogether, these results illustrate the pivotal role of Sox9 in the direct regulation of HK1 activities. Phosphorylated Sox9, which exhibits enhanced transcriptional activity, leads to sustained high HK1 activation under pathological conditions, enhancing glycolytic pathway in astrocytes and contributing to NeP induction and pathogenesis.\u003c/p\u003e\n\u003ch3\u003ep-SOX9 drives pathogenic astrocyte clusters\u003c/h3\u003e\n\u003cp\u003eTo further explore the influence of Sox9 on the emergence of detrimental astrocyte subclusters during NeP pathogenesis, we analyzed the heterogeneous astrocyte properties in response to increased Sox9\u003csup\u003eS181D\u003c/sup\u003e in Sham and \u003cem\u003eSox9\u003c/em\u003e knockdown in SNI, linking to HK1-mediated glycolytic pathway. First, we found that reduced p-Sox9 levels significantly alleviate the hypertrophic GFAP\u003csup\u003e+\u003c/sup\u003e populations in SNI and decrease the gene expressions associated with pro-inflammation and neurotoxic and astrocyte reactivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). We also detected a significant elevation of an anti-inflammatory gene, TGF-β. In contrast, overexpression of SOX9\u003csup\u003eS181D\u003c/sup\u003e in Sham induced reactive astrocytes in the dorsal spinal cord along with a set of genes encoding for pathogenic activities during pain pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). By combining the scRNA datasets from Sham and SNI, we revealed five astrocyte subclusters similar to those reported above (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Similarly to SNI or Sham treated with \u003cem\u003eHK1\u003c/em\u003e overexpression (SHAM\u0026thinsp;+\u0026thinsp;\u003cem\u003eHK1\u003c/em\u003eOE), increased Sox9\u003csup\u003eS181D\u003c/sup\u003e reduced homeostatic and inflammatory resolving astrocytes subcluster, Astro 3, while induced neuroinflammatory astrocytes subset (Astro1) with \u003cem\u003eHK1\u003c/em\u003e enrichment, which express genes associated with pain signaling (e.g., C3, \u003cem\u003eCfb, Clu, CxCl2\u003c/em\u003e). Notably, Sox9 activities also influenced Astro 2, defined as a neurodegenerative-associated subcluster. Increased p-Sox9 significantly expanded Astro 2 populations, indicating the border detrimental effects of p-Sox9 in promoting injury-responsive astrocytes subclusters than HK1. Conversely, \u003cem\u003eSox9\u003c/em\u003e knockdown caused a major contraction of Astro 1 and the depletion of Astro 5, confirming a suspended reactivating process and formation of neuroinflammatory properties (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). Subsequent trajectory inference analysis clearly shows that the hierarchy of astrocytic phenotypes resulted from homeostatic/inflammatory resolving cluster (Astro 3, expressing \u003cem\u003eKcni8\u003c/em\u003e and \u003cem\u003eCox4i2\u003c/em\u003e) to intermediate stage including transitioning Astro 4 (Proliferating) or early reactivating Astro 5 (transiently upregulated glutamate transmitter in pain), then to more terminally neuroinflammatory Astro1 or neurodegenerative/demyelinated Astro 2 (e.g., \u003cem\u003eS100b, Cryab\u003c/em\u003e, and \u003cem\u003eAplp1\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF), indicating the differential pathway in forming deleterious astrocytes clusters during pain development. Maximal differences in \u003cem\u003eSox9\u003c/em\u003e, glycolytic genes, and genes for pathogenic astrocyte activities in promoting nociceptive signaling were observed mostly in Astro 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). Collectively, these data indicated that phosphorylation of Sox9 drives the formation of detrimental astrocyte subclusters, and is important for HK1-mediated pathogenic astrocytes in pain.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe catalytic activity of HK1 induced by p-Sox9 drives histone lactylation for genes controlling neuroinflammatory astrocyte properties\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNext, we asked how enhanced glycolysis driven by p-Sox9-HK1 promotes detrimental astrocyte properties. Histone lactylation was recently identified as an epigenetic modification that is controlled by the amount of lactate content in cells\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Similar to histone acetylation, histone lactylation can directly stimulate gene transcriptions and alter the cellular status and functions, such as controlling the pro- or anti-inflammatory status of macrophages/microglia\u003csup\u003e37, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. The increased production of lactate in detrimental astrocytes prompted us to examine whether lactylation could affect gene expression inducing astrocyte pathogenic activities under pain conditions. Indeed, western blotting analysis of acid-extracted histones showed an increase in the levels of Pan-lysine lactylation (Pan Kla) after injury, which is abolished by glycolytic inhibitor, 2-DG, delivered via intrathecal injection (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). To examine specific changes in histone lactylation in astrocytes that are associated with altered glycolysis, we performed immunofluorescence co-staining of H3K18la, H3K9la and H3K14la along with GFAP\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. All of them can be detected in spinal astrocytes homeostatically and were significantly activated in astrocytes upon injury, with C3 elevation and responsive to glycolytic inhibition (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC, \u003cb\u003eExtended data Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA and S2B\u003c/b\u003e). Further investigation into histone lactylation revealed that HK1 or p-Sox9 activation predominantly induces H3K9la expression, with minor effects on H3K9la or H3K14la in astrocytes. Moreover, knocking down \u003cem\u003eHK1\u003c/em\u003e in \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e expressed astrocytes abolished H3K9la elevation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD, \u003cb\u003eExtended data Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eE and S2F\u003c/b\u003e). These data suggest that H3K9la is the most prevalent differentially affected histone lactylation modification in the dorsal astrocytes, controlled by the p-Sox9-HK1-lactate axis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate the functional link of H3K9la with detrimental astrocyte properties in promoting NeP, we performed genome-wide CUT\u0026amp;Tag analysis using antibodies against H3K9la to identify candidate genes regulated by H3K9la in Sham and SNI. Analysis of k-means clustering partitioned the dataset into four distinct clusters, revealing obvious enrichment of H3K9la peaks in clusters 1 and 2, which predominantly bind within 1.5 kb of transcription start sites (TSS), spanning 17.06% promoter regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eE and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eF). Gene ontology biological process (GOBP) terms and KEGG pathways of higher H3K9la binding peaks at the gene promoter showed that these genes are enriched in cytokine/chemokines and signaling pathways for NF-kB, JAK-STAT and PI3K-AKT, which are involved in regulating pro-inflammation and glial activation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eG \u003cb\u003eand Extended data Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA\u003c/b\u003e). Specifically, we found that increased H3K9la peaks at the promoters of key genes that promote astrocytes\u0026rsquo; deleterious activities and neuroinflammatory phenotypes in SNI (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eH \u003cb\u003eand Extended data Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB\u003c/b\u003e). Consistently, a quantitative chromatin immunoprecipitation (qChIP) analysis indicated that the H3K9la levels on \u003cem\u003eGfap\u003c/em\u003e, \u003cem\u003eC3\u003c/em\u003e, and \u003cem\u003eCfb\u003c/em\u003e promoters are significantly elevated in astrocytes from SNI and overexpressions of \u003cem\u003eHK1\u003c/em\u003e and \u003cem\u003eSox9\u003c/em\u003e\u003csup\u003e\u003cem\u003eS181D\u003c/em\u003e\u003c/sup\u003e rats compared with Vector control or Sham. Furthermore, H3K9la enrichment in the promoter regions can be abolished upon \u003cem\u003eHK1\u003c/em\u003e knockdown in astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eI). Collectively, these results demonstrate that p-Sox9-HK1 drives astrocytic histone acetylation, which activates key genes regulating deleterious astrocyte properties through H3K9la modifications, contributing to NeP pathology.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAstrocytes are central players in a myriad of processes in the healthy and diseased CNS, ranging from metabolism to immunity and degeneration. The analysis of the heterogeneity of microglia and macrophages has provided important insights into immune responses in pain pathogenesis. Despite astrocytes have been identified as a key driver for pro-longed neuroinflammation in the dorsal spinal cord, little is known about astrocyte heterogeneity and its regulation in NeP development. Our study identified differential astrocyte subclusters under physiological and pathological pain conditions and uncovered a novel phosphorylated Sox9-HK1-H3K19la signaling axis that controls the emergence of deleterious astrocyte subsets, which promote neuroinflammatory responses, leading to pain induction and development.\u003c/p\u003e \u003cp\u003eIdentifying astrocyte subtypes with distinct functions in pain pathologies is a major step toward better therapeutic strategies, which involves targeting detrimental clusters while preserving properties in the pro-resolution and neural repair phase for treating NeP. Our work shows that nerve injury-induced two major deleterious astrocyte subclusters, Astro 1 and 2, and dampened Astro 3. Astro 3 is a predominant population in the dorsal spinal cord under normal conditions, with enriched genes for astrocyte homeostatic functions and pain-resolving immune mediators. In contrast, Astro 1 is characterized by genes for pro-inflammatory and neurotoxic signaling, highly associated with nociceptive signaling for central sensitizations. Astro 2 is defined by its neurodegenerative and demyelinating nature and may also include an astrocyte-like NG2 glia subpopulation, potentially exerting neuroprotective functions in response to traumatic injury \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur further scRNA analysis highlighted glycolysis as a common GO term enriched in detrimental astrocyte cluster Astro 1, as well as in two transiting/proliferating subclusters, Astro 4 and 5. The large glycolytic capacity of the CNS is primarily attributed to astrocytes, crucial for supporting neuronal activities and metabolism under homeostatic conditions. In response to inflammatory stimuli, astrocytes could increase their rate of glycolysis to prevent ATP depletion and cell death in vitro\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Enhanced astrocytic glycolysis, beneficial in certain neurodegenerative disorders like Alzheimer's disease, can improve cognition by supporting neuronal survival and axon growth in the brain\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. However, prolonged high astrocytic glycolysis is harmful in pain pathology. Notably, we found that HK1, the first catalytic enzyme in converting glucose into glucose-6-phosphate irreversibly, is enriched in Astro1 and aberrantly activated from the early stage of pain induction, persisting over chronic phases. The heightened glycolysis induced by HK1 exerts specific effects in controlling the emergence of the detrimental Astro 1 cluster, driving immunopathogenic activities in the dorsal horn and ultimately contributing to the development of NeP. The finding aligns with a recent study demonstrating \u003cem\u003ePTG\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u0026minus;\u003c/em\u003e\u003c/sup\u003e mouse inflammatory pain model reduces glycogen accumulation in astrocytes, leading to decreased pain-related behaviors and facilitating a quicker recovery. Additionally, this model showcases a reduced glycolytic capacity as compared with the WT dorsal spinal cord network\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur studies also identified a novel regulatory link between the astrocytes specifier, Sox9 and glycolysis, potentially explaining differential metabolic programs adopted by astrocytes and neurons during development and homeostasis. Sox9 belongs to a member of the SRY-like HMG-box family, which functions as a key transcriptional regulator for the specification of astrocytes, neural crest and chondrocytes during development\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. In adults, Sox9 expression is specifically expressed in na\u0026iuml;ve astrocytes and upregulated in reactive astrocytes following brain and spinal cord injury\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Previously, ours and others found that Sox9 can undergo phosphorylation, leading to distinct effects on cellular behavior and activities \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Here, we found that Sox9 could directly regulate HK1 expressions, contributing to glycolysis in astrocytes. Intriguingly, in response to initial nerve injury, Sox9 experiences abnormal phosphorylation, resulting in enhanced nuclear translocation and transcriptional activation, which causes aberrant activation of HK1. This phosphorylated Sox9 not only contributes to the emergence of the HK1-mediated neuroinflammatory astrocyte cluster 1, but also induces Astro 2, which represents a property with neurodegenerative and demyelination nature. It is plausible that the phosphorylation of Sox9 may trigger different downstream signaling pathways depending on the cellular context, resulting in the development of distinct astrocyte subtypes.\u003c/p\u003e \u003cp\u003eNotably, the intimate link between transcriptional regulation of Sox9 and glycolytic changes also ha ve been implicated in a few studies. For example, \u003cem\u003eSox9\u003c/em\u003e-haploinsufficient mice exhibit metabolic abnormalities with impaired glucose tolerance\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The ectopic expression of two key glycolytic enzymes, HK2 and LDHA, has been shown to promote astrocyte differentiation from human neural stem cells via enhanced aerobic glycolysis \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, resembling the functions of Sox9. It is interesting to note that phosphorylated Sox9 is required to regulate neural crest delamination\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, with recent research from Bhattacharya et al indicating that delaminating neural crest cells exhibit heightened glycolytic activities to facilitate cell migration\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, revealing a strong link between phosphorylation of Sox9 and increased cellular glycolytic activity. The interaction between Sox9 and Hexokinase mediated glycolytic activities may represent a common regulatory axis in diverse cellular contexts in health or disease.\u003c/p\u003e \u003cp\u003eFinally, we uncovered a significant mechanism underlying altered energy metabolism and epigenetic regulation in pain pathogenesis, which through H3K9la induction at the promoter regions of neuroinflammatory-regulatory genes for inducing specific types of deleterious astrocytes in NeP. Differential levels of metabolites, such as acetyl-CoA, ATP, and lactate can serve as substrates for histone modifications that directly stimulate gene transcription from chromatin. Recently, histone lactylation has emerged as a novel epigenetic alteration mediated by cellular lactate levels \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. A few studies have highlighted how accumulating such substrates significantly impacts immune cell functions, such as microglia and macrophages, potentially exacerbating neurodegenerative progression \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Despite pain status being highly associated with metabolic diseases, diabetes, excess glucose intake, and increased lactate \u003csup\u003e\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, the link and molecular understanding of such knowledge are less documented. In our study, we found that heightened glycolysis in SNI triggers increased lactate production, resulting in elevated histone lactylations, including H3K18la, H3K9la, and H3K14la modifications, in astrocytes. The p-Sox9-HK1-lactate axis mainly contributes to H3K9la inductions in dorsal spinal astrocytes, with less effects on H3K18la and H3K14la. Analysis using Cut\u0026amp; Tag further indicates that H3K9la is highly enriched at the promoters of key genes responsible for inducing detrimental astrocyte phenotypes and regulating pathogenic activities, thereby leading to a sustained neuroinflammatory state in NeP. Additionally, our results imply that the complexity of histone lactylation may exist in astrocytes, possibly involving other increased histone lactylation marks, such as H3K18la and H3K14la, which may implicate distinct regulators or different subtypes of astrocytes warranting further investigation. Our study offers valuable insights to aid future epigenomic studies on pain pathogenesis.\u003c/p\u003e \u003cp\u003eIn summary, we have revealed that phosphorylated Sox9 induces aberrantly high HK1 activities that affect gene expression via histone lactylation in astrocytes. This regulatory mechanism promotes detrimental astrocyte properties in the dorsal horn, thereby contributing to NeP development. These findings may guide novel therapeutic approaches for the modulation of astrocyte pathogenic activities in other neurologic disorders.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of study\u003c/h2\u003e \u003cp\u003eWhile our research uncovers the emergence of neuroinflammatory astrocyte subtypes mediated by p-Sox9-HK1, we have also observed the development of another potentially detrimental astrocyte subset, Astro 2, during NeP progression. Further investigations are warranted to explore the functional roles of this subset, which will provide deeper insights into the mechanisms of astrocyte heterogeneity in the initiation and maintenance of NeP. Another limitation is that we found SNI-induced other forms of lactylation, specifically H3K18la and H3K14la, in astrocytes. Further research efforts may reveal previously unidentified genes or mechanisms associated with the regulation of these histone lactylations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKEY RESOURCES TABLE\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eREAGENT or RESOURCE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSOURCE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIDENTIFIER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eAntibodies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-SOX9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMerck Millipore\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# AB5535\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-SOX9 (phospho S181)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab59252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMouse Monoclonal anti-GFAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab10062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Monoclonal anti-Hexokinase I (C35C4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eCell Signaling Technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# CST-2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMouse Monoclonal anti-C3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSanta Cruz Biotechnology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# sc-28294\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMouse Monoclonal anti-S100 (\u0026beta;-Subunit)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSigma-Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# S2532\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Polyclonal anti-NFIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eATLAS ANTIBODIES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# HPA006111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-TNF alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab6671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-IL-1 beta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab9722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Monoclonal anti-IL-6 (D5W4V) XP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eCell Signaling Technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# CST-12912\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-IL-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab9969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit polyclonal anti-TGF beta 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab92486\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMouse Monoclonal anti-beta actin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSigma-Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# A2228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Polyclonal anti-Histon H3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eCell Signaling Technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# CST-9715\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Monoclonal anti-Lactyl Lysine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePTMBIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# PTM-1401RM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Monoclonal anti-L-Lactyl-Histone H3 (Lys9)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePTMBIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# PTM-1419RM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Polyclonal anti-L-Lactyl-Histone H3 (Lys14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePTMBIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# PTM-1414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRabbit Monoclonal anti-L-Lactyl-Histone H3 (Lys18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePTMBIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# PTM-1406RM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eGFAP Monoclonal antibody (GA5), eFluor\u0026trade; 660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher/Invitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 50-9892-82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eBacterial and virus strains\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eAdeno-associated viruses, genus Dependoparvovirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eBiological samples\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eTrypan Blue Solution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eGibco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 15250061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eFicoll-Paque (Percoll)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eGE Healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 45-001-748\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRBC lysis buffer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 420301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eHBSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eDAPI(4\u0026rsquo;,6-Diamidino-2-Phenylindole, Dihydrochloride)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermofisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 1306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRIPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 87788\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eHalt\u0026trade; Protease and Phosphatase Inhibitor Cocktail (100X)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 78440\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eCritical commercial assays\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eHexokinase Activity Assay Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# ab136957\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eL-lactate assay kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# MAK329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePyruvate Assay Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# MAK071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eCyQUANT cell proliferation assay kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# C7026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMagnetic IP/Co-IP kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 88804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eNuclear and Cytoplasmic Extraction Reagents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 78833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePierce\u0026trade; Magnetic ChIP Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 26157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eNeural Tissue Dissociation Kits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMiltenyi Biotec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 130-092-628\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMiltenyi Neural Tissue Dissociation Kit (P)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 14175095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRNA extraction kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermoFisher/Invitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# AM1931\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eQuickChange Site-Directed Mutagenesis Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAgilent Technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# 200519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eExperimental models: Organisms/strains\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eRat: Sprague Dawley\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eCCMR of the University of Hong Kong\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eRecombinant DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-mCherry-5\u0026apos;miR-30a-shRNA(scramble)-3\u0026apos;-miR30a-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eVectorBuilder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-EGFP-5\u0026apos;miR-30a-shRNA(SOX9)-3\u0026apos;-miR30a-WPREs, AAV9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-EGFP-WPRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-SOX9(S64A, S181A)-EGFP-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-SOX9(S64D, S181D)-EGFP-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-mCherry-5\u0026apos;miR-30a-shRNA(scramble)-3\u0026apos;-miR30a-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-GFAP-mCherry-5\u0026apos;miR-30a-shRNA(HK1)-3\u0026apos;-miR30a-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: rAAV-CMV-DIO-HK1-2A-mCherry-WPREs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBrainVTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-basic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePromega\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat# E1751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-HK1-Binding Site 1 (promoter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThis manuscript\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-HK1-Binding Site 2/3 (promoter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThis manuscript\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-HK1-Binding Site 4/5 (promoter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThis manuscript\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-HK1-Mut-Binding Site 1 (promoter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThis manuscript\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ePlasmid: PGL3-HK1-Mut-Binding Site 2/3 (promoter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThis manuscript\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #N/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eSoftware and algorithms\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eFIJI ImageJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eFIJI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://fiji.sc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eFlowJo v10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBD Biosciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.flowjo.com\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eFileZilla v3.42.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eFileZilla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://filezilla-project.org/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003ebcl2fastq\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eIllumina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://support.illumina.com/sequencing/ sequencing_software/bcl2fastq-conversion-\u003c/p\u003e\n \u003cp\u003esoftware.html\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003epheatmap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eKolde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://cran.r-project.org/web/ packages/pheatmap/index.html\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eggplot2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://cran.r-project.org/web/ packages/ggplot2/index.html\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eCell Ranger Software v2.1.1 (February 26, 2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e10x Genomics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://support.10xgenomics.com/ 2018) single-cell-gene-expression/software/\u003c/p\u003e\n \u003cp\u003edownloads/2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eR version 4.1.3 (2022-03-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.r-project.org\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eR Studio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003ePosit Software\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://posit.co/download/rstudio-desktop/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eBioconductor v3.9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBioconductor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.bioconductor.org\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eSeurat v2.3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.satijalab.org/seurat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMonocle3 alpha v2.99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.github.com/cole-trapnell-lab/ monocle-release/tree/monocle3_alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eKEGG Pathway Database\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.genome.jp/kegg/pathway.html\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eBD FACSDivaTM Software v8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBD Biosciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.bdbiosciences.com\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eGraphPad Prism v9.4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eGraphPad Software\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://www.graphpad.com/features\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eSnapeGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eSnapGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://www.snapgene.com\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eIGV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eIntegrative Genomics Viewer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://igv.org/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eMicrosoft\u0026acirc; Excel\u0026acirc; for Microsoft 365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMicrosoft Corporation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ewww.office.com\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eNovaSeq 6000 System\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eIllumina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #20012850\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eBD FACSAriaTM III Cell Sorter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBD Biosciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #648282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eNanoDropTM One (Thermo Scientific)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eThermo-Fisher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #ND-ONE-W\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eLightCycler 480 II Real-Time PCR System\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eRoche Life Science\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eCat #05015243001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003eCLARIOstar Plus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBMG LABTECH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ehttps://www.bmglabtech.com/en/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eKey table for qPCR primers:\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGENE NAME\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFORWARD (5\u0026rsquo; to 3\u0026rsquo;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eREVERSE (5\u0026rsquo; to 3\u0026rsquo;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimers for rat samples\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;-actin\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCAACTGGGACGATATGGAGAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGTTGGCCTTAGGGTTCAGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eSox9\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTCTACTCCACCTTCACCTACAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTGTGTGTAGACGGGTTGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eGfap\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTGGCCACCAGTAACATGCAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCAGTTGGCGGCGATAGTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHk1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGAGCGGATGTGGTCAAGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCATGGTCCCTACTGTGTCATTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eGpi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCTGGGCATCTGGTATATCAAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eATGTCACCCTGCTGGAAATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePfkp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGGTGCGCATGGGAATATACA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCCACTTGGCTTCCACAATA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eTpi1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCTGGCATGATCAAGGACTTAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGGATAGGGCATGGTTCACTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eAldoa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTGGCGCTGTGTGCTAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGGCTCCACAATGGGTACAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eGapdh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCCCCAATGTATCCGTTGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTAGCCCAGGATGCCCTTTAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePgk1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCACAGAAGGCTGGTGGATTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCAACTTTAGCTCCTCCCAAGATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePgam1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCACTGCCCTTCTGGAATGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCCTCCAGATGCTTGACAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eEno1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGATGGACGGCACAGAGAATAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTCGGCAATGTGACGGTAAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePkm\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCATCCTGTGGCTGGACTATAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTCAGCACCTTTCTCCTTCAC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eLdha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGACTTGGCCGAGAGCATAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGGAAGACATCCTCCTTGATTCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePfkbp3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTACCTCAACTGGATAGGTGTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eAGGGCGGAAGAAGTTGTAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eIdh2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eAACACCGACGAGTCCATTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTCAAGTAGAGCGGCCATTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eSdha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTTTCCTACCCGCTCACATAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGCCTTTCACGGTGTCATAGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eMdh2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eAACCCAGTTAACTCCACCATC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eAGGGTTGTCACACCGAATATC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eIL-1\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTTCCTAAAGATGGCTGCACTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTGACTTGGCAGAGGACAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGAAGTTAGAGTCACAGAAGGAGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGTTTGCCGAGTAGACCTCATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eTnf-\u0026alpha;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eACCTTATCTACTCCCAGGTTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGGCTGACTTTCTCCTGGTATG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eCcl2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGTCTCAGCCAGATGCAGTTAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTGCTGGTGATTCTCTTGTAGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eCcl7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eAACCAGATGGGACCAATTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCACCGACTACTGGTGATCTTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eCxcl10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCATTCCTGCAAGTCTATCCTGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGCTCTTGATGGCCTCAGATT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eIl-4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGTCACCCTGTTCTGCTTTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGACCTGGTTCAAAGTGTTGATG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eTgf-\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTGAACCAAGGAGACGGAATAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGTTTGGGACTGATCCCATTGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eStat3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eACCCAGATCCAGTCTGTAGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGTTGGTAGCGTCCATGATCTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eC3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTGGAAAGGAGGATGGACAAAG\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTGGCAGCTGTACTTCATAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eS100a10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTGCTCATGGAAAGGGAGTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCACTGGTCCAGGTCTTTCATTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eAldoc\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGGCTGCTACTGAGGAGTTTATC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCATCTCCACTGCCTTCATATT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eS100\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCAGGAAGTGGTGGACAAAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCATGGAGACGAAGGCCATAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eIl-17\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eAAACGCCGAGGCCAATAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGAAGTGGAACGGTTGAGGTAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eCfb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTCGGGCTCCATGAATATCTAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTAACTCGCCACCTTCTCAATC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eMx1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTCACCTCCCACATCTGTAAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGTATGTCTGCTCCGTACTTCTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eVim\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGCCCTTGAAGCTGCTAACTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eATTGAGCAGGTCCTGGTATTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eAldh1l1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGCTCCATCATCTACCATCCATC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTGGTGAAGCCTCCTTTCTTATC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003ePGL3-seq\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTAGCAAAATAGGCTGTCCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1_bst-1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTGCGCTCTCCAGACCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCGCTGCAGAGGAGACTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1_bst-2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGATGGAGCTGATGCCTACAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eTTCCCGAGTCCGTTCTATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1_bst-3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eGCTGGGTTTGCTTAGCTTTAAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTATGTTGCAGTCCTGGTCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1_bst-4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCAGAGGTCTGTAGGTTGAATGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eATAGTGATGGCTGAAGGTTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1_bst-5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCACACACACACGCTACCAATA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGAGCTGGCCGAAGTACATTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCCAAGCTTGCTCCTCAGTAGCCCTGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCGCTCGAGTTCTCCAACAGTGTGGATGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-2/3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCCAAGCTTGCGCTGGGTTTGCTTAGCTTTAAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCGCTCGAGTTCCCGAGTCCGTTCTATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-4/5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCCCAAGCTTGCCATTGTGTGCAGTTTCTCTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCGCTCGAGGTTTGTTGGCTAAGGGTTGTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-mut-1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eCTGGCGGTTGTCACCCTCCCGGGGACCGGAGCTCCGAGGTCTGGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCCGGCCCACTTCCTCAGTCCCCGCTAGCTGCAAGTCTCCTCTGCAGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-mut-2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTACCTCCCATCTAATCTATTAGATACCGGTCTTTATGCTCTTTCAGAAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eCTCTCATAGAACGGACTCGGGAACTCGAGCCCGGGCTAGCACGCGTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cem\u003eHK1-luci-bst-mut-3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 265px;\"\u003e\n \u003cp\u003eTAAGCAAACCCAGCGCAAGCTTGGCATTCCGGTACTGTTGGTAAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eGCTTTAACGCCGGTGACCTAGCCGCTCTGTGCAGTTTCTCTTCTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEXPERIMENTAL MODEL AND SUBJECT DETAILS\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRat\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale adult Sprague-Dawley (SD) rats aged between 4 to 6 weeks and weighed approximately 230 grams were sourced from the Centre for Comparative Medicine Research at the University of Hong Kong. It\u0026apos;s important to note that this institution is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. All experimental and handling protocols were conducted with the prior approval of the Faculty Committee on the Use of Live Animals in Teaching and Research (CULATR), with reference numbers 5457-20 and 5859-21. The rats were maintained in a temperature-controlled environment at 25\u0026deg;C with a 12-hour light and 12-hour dark cycle, housed and used following the guidance of CCMR. They are free to access the food and water. Before any procedures, all rats were randomly assigned to their respective groups and allowed to acclimate in new cages for 2 to 3 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of nerve injury model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe injury model of spared nerve injury (SNI), originally described by Decosterd and Woolf in 2000 \u003csup\u003e54\u003c/sup\u003e, is utilized to mimic human NeP associated with peripheral nerve injury. This model can induce early (\u0026lt;24 hours) and long-lasting (\u0026gt;6 months) neuropathic pain-like behaviours (e.g., allodynia and hyperalgesia) \u003csup\u003e13\u003c/sup\u003e\u003csup\u003e,\u0026nbsp;54\u003c/sup\u003e, which can be evaluated using standard methods (e.g., Von Frey test, Hargreaves test, and Two Temperature Preference test). In this laboratory animal model, animals were anesthetized by intraperitoneal (i.p.) injection of 75-100 mg/kg of Ketamine (100mg/ml), 10mg/kg of Xylazine (20mg/ml) prior to surgery. An incision was made in the skin on the lateral surface of the right thigh of the rat, exposing the terminal branches of the sciatic nerves\u0026mdash;specifically, the sural, common peroneal, and tibial nerves\u0026mdash;by dissecting the biceps femoris muscle. The sural peroneal and tibial nerves were tightly ligated with 4-0 silk at the trifurcation point, then severed distally to the knot, with the distal nerve ends trimmed approximately 3\u0026ndash;5 mm. The sural nerve remained untouched during the surgical procedure. In the SHAM-operated rats, the sciatic nerve was not to be ligated nor cut \u003csup\u003e55\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc174372821\"\u003e\u003cstrong\u003eIntraspinal virus injections\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVirus was delivered into SDH of rats as previously described \u003csup\u003e56\u003c/sup\u003e. Rats will be subjected to subcutaneous injection with Meloxicam (1mg/kg) and Buprenorphine (0.03 to 0.05 mg/kg) a day before the surgery to reduce the pain during the procedure. All surgical procedures will be performed under anaesthesia by Ketamine and Xylazine (Ketamine: Xylazine=2:1; 1.3\u0026times;BW, body weight) administrated via intra-peritoneal injection. Lidocaine hydrochloride (0.58% or 1.2 of 0.5% Lidocaine hydrochloride \u0026times;BW) can be locally applied to reduce the pain. The hair on the lumber spine will be removed via depilatory cream and shavers. Iodophor and alcohol are used to scrub the skin and avoid infection. The skin will be allowed to air dry 30s. A small incision was performed on the skin to expose the T12-L1 of the spine. The muscle on the spine may be incised and few muscles will be removed to expose the spine. \u0026nbsp; A midline incision was meticulously made along the left lumbar vertebrae, extending until the spinal cord was visible between the intervertebral spaces of the T12 and T13 vertebrae. To reduce trauma, no laminectomy was carried out. The dura and arachnoid will be opened using 33-gauge bevel needle. Later, KDS Legato 130 Syringe Pump (RWD) with a 10ul Hamilton microinjection syringe, equipped on the stereotaxic apparatus, is used to deliver AAV9 virus for gene knockdown or overexpression, as well as control AAV. The 33gauge blunt needle is inserted into the spine and touched the spinal cord for injection and the injection rate is 0.2ul/min. After infusion, the microinjection syringe was left in place for 5 minutes before being gently withdrawn. After injection, the muscle on the spine will be sutured with 4-0 absorbable suture. Then, 4-0 Nylon sutures is used for skin suture. Baytril (Enrofloxaim, 6.6mg/kg, intramuscular) will be administrated immediately post-surgery and then daily for 3 days. The analgesic, buprenorphine (0.05mg/kg, subcutaneous) will be delivered post-surgery every 12 hours for 3 days and then daily injection with Meloxicam (1mg/kg) up to a week.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntrathecal drug delivery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntrathecal drug delivery, commonly referred to as the \u0026quot;pain pump,\u0026quot; involves a small pump that administers pain medication directly to the spinal cord, offering more efficacy compared to oral pain medications. The pump is surgically implanted beneath the abdominal skin and dispenses pain medication through a catheter to the region surrounding the spinal cord. \u0026nbsp;The protocol was referred previous method \u003csup\u003e57\u003c/sup\u003e. In summary, all rats were initially anesthetized with 5% isoflurane, which was maintained at 2% throughout the surgical procedure. Following the shaving and sterilization of the surgical site using povidone-iodine, a skin incision approximately 3 cm in length was created over the L2-3 lumbar spinal cord region. 2-Deoxy-D-glucose (2-DG, Sigma, D8375) for inhibition of glycolysis, or IPA-3 (APExBIO, B2169) Romidepsin (FK228) (AbMole, M2007 and MOLNOVA, M11164) were gently administered into the L2\u0026ndash;3 intervertebral space utilizing a 1 mL syringe. The quantity of administered drugs was determined based on prior references. After the injection, 4-0 Nylon sutures is used for skin suture. Baytril (Enrofloxaim, 6.6mg/kg, intramuscular) will be administrated immediately post-surgery and then daily for 3 days. The analgesic, buprenorphine (0.05mg/kg, subcutaneous) will be delivered post-surgery every 12 hours for 3 days and then daily injection with Meloxicam (1mg/kg) up to a week.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVon Frey Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor behavioural experiments, blind measurements were conducted to evaluate the pain sensitivity to stimulus for all treatments. The sample size is at least five, and Sprague Dawley (SD) rats of 230g born within 4-6 weeks were used in the same behavioural experiments.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTo assess mechanical allodynia, rats were tested as previously described \u003csup\u003e58\u003c/sup\u003e. Briefly, after habitation in a quiet room, an animal containment system comprising a transparent plastic chamber (70 \u0026times; 24 \u0026times; 15 cm, Designage Ltd. Hong Kong) placed on a wire mesh table is used during the assessment. Each animal is placed in the chamber, allowing access to the plantar surface of the hind paw through the metal mesh floor (70 \u0026times; 36.5 \u0026times; 42 cm, The Sun Furniture Manufacturing Co. Hong Kong). The animals are given 30 minutes to accommodate the environment for 30 minutes before testing. Throughout the examination, plastic filaments are applied perpendicularly to the plantar surface of the hind paw with constant pressure. Testing was conducted employing a set of calibrated Semmes-Weinstein monofilaments (commonly called Von-Frey Hairs) using the Up-Down method \u003csup\u003e58\u003c/sup\u003e, beginning with a 4.0 g filament (RWD, Aesthesio). The 50% paw withdraw threshold (PWT) was assessed for each rat on one or both hind paws. Every filament was gently placed on the hind paw\u0026apos;s plantar surface for 5 seconds or until a reaction like abrupt withdrawal, shaking, or limb licking occurred. Instances of rearing or regular ambulation during filament application were disregarded. Filaments were used at intervals of five minutes until thresholds were established. Each measurement was conducted twice per rat, and the average value was considered the final PWT value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlantar Heat Test (Hargreaves)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess heat-thermal hyperalgesia, the ipsilateral hind paw of the animal will be measured individually using a thermal stimulus apparatus (Ugo Basile, Varese, Italy). The the beam intensity was calibrated and set to a baseline latency of 8\u0026ndash;12 s before the test. It is noted that the administration duration of stimuli is very transient (usually less than 20 secs), and therefore, no severe injury will be generated. The determination of paw withdrawal latency will involve averaging five measurements per paw. The hind paws will be evaluated alternately, ensuring a minimum 5-minute interval between successive stimuli on the same hind paw. Responses will only be considered as withdrawal if there are swift hind paw movements, with or without hind paw licking away from the stimulus. Movements related to locomotion or weight shifting will not be classified as a response, prompting a re-test for that trial.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTwo Temperature Preference Analysis (TTP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo hot/cold plates from BIO-CHP-ER, obtained from RWD Limited Company, were positioned sequentially to enclose adjacent thermal surfaces at varying temperatures within a unified chamber (165 x 165 mm). The temperature of each platform was regulated within \u0026plusmn; 0.11\u0026deg;C using SMART 3.0 (PanLab) software. Rat movement between the two plates was monitored via a video tracking system over a 6-minute period. Thermal preference was determined by calculating the total time spent on each plate \u003csup\u003e59\u003c/sup\u003e\u003csup\u003e,\u0026nbsp;60\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo evaluate rats\u0026apos; responses to different temperatures, one plate, designated as the reference plate, was set to 30\u0026deg;C for hot temperature testing, while the other plate, the test plate, was adjusted to 45\u0026deg;C. For cold temperature assessment, the reference plate stayed at 30\u0026deg;C, while the test plate was set to 20\u0026deg;C. Rats were gently positioned in the apparatus, aligning their bodies with the separation line between the plates and their paws situated on each plate. Subsequently, rats were allowed to move freely between plates, with their movements discreetly recorded by an overhead camera. The number of transitions between plates were recorded, and the time spent on the test plate was calculated. The equipment was methodically cleaned after each rat session, and the order of the reference and test plates were shuffled between trials to prevent bias. Prior to experimental testing, rats underwent habituation to the conditions to minimize stress. This involved spending 5 minutes daily for two days on the plates at 30\u0026deg;C. After this familiarization period, rats were expected to spend a similar duration on each plate during a 6-minute session, ideally between 300-360 seconds. Rats deviating significantly in time spent on either plate, making only one or no transitions, were excluded. To mitigate learning effects, the reference and test plate temperatures were switched for subsequent trials. Each rat was tested twice per parameter set, with re-habituation between trials. Video analysis via an automated tracking system (Bioseb) quantified the percentage of time spent on each plate \u003csup\u003e61\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcetone test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe acetone evaporation test is referred to the published protocol \u003csup\u003e62\u003c/sup\u003e. It is the good method to measure the behaviour of cold allodynia triggered by evaporative cooling \u003csup\u003e63\u003c/sup\u003e\u003cu\u003e\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u003c/u\u003e\u003csup\u003e64\u003c/sup\u003e. Simply, rats were placed on the metal mesh floor, and acetone was sprayed on the plantar surface of the left hind paw. The behavior was record and scored. (0= no response, 1= brief flick, 2= raise more than 1s, 3= biting and flicking)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein extracts, SDS-PAGE, and Western blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor western blotting, harvested L3-6 left dorsal spinal cord tissue was transferred into an ice-cold glass homogenizer with 0.2ml RIPA lysis buffer (Thermo Fisher Scientific, #87788), supplemented with 1X protease inhibitor (Thermo Fisher Scientific, #78440). Tissues were slowly triturated using the homogenizer on ice and rotated every 10 min during the mechanical dissociation step. The protein concentrations were determined through the application of the BCA assay. 2X loading buffer was added to the cell lysate, 95\u0026deg;C boiled for 8min and 30mg of protein was used for SDS-PAGE.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEqual amounts of protein (30 \u0026mu;g) were loaded into the wells of the SDS-PAGE gel, alongside the molecular weight marker (BIO-RED, #161-0374). Run the gel for about 20mins at 100V in running buffer (25 mM Tris base, 190 mM glycine, 0.1% SDS, pH 8.3) until the protein ladder reaches the borderline of stacking and separating gel, and then adjust the voltage to 120V for 1h. After the protein marker was separated to a suitable range, the protein was transferred from the gel to the PVDF membrane in the pre-cold transfer buffer (25 mM Tris base, 190 mM glycine, 20% methanol, pH8.3) for 1.5h at 100V on ice. Before preparing the stack, the PVDF membrane was activated with methanol for 2mins and rinsed in the transfer buffer. Then, block the membrane in blocking buffer (4% milk supplemented in the 1X PBS) at room temperature for 1 hour. After twice washing with 1X TBST (1X TBS, supplemented with 1% Triton X100), incubate the membrane overnight at 4\u0026deg;C with primary antibody appropriately diluted in blocking buffer. Wash the membrane twice using 1X TBST, incubate the membrane with the recommended dilution of Horseradish peroxidase (HRP)-conjugated secondary antibody in blocking buffer for 1 hour at room temperature. Wash the membrane twice using 1X TBST, and then incubate with HRP chemiluminescent substrates (Bio-Rad, # 1705062) chemiluminescent substrates and acquire images in darkroom.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA isolation, cDNA synthesis and qPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA extraction kit (Thermo Fisher Scientific, AM1931) was purchased to get total RNA from GFAP-labelled sorted cells. Briefly, cells collected from FACS were centrifuge at\u0026nbsp;750g at 4\u0026deg;C for 5 min to get cell pellet. Resuspended cell pellet by vortexing vigorously in 100\u0026mu;l Lysis Solution and putted on ice for 5min. Then, 50\u0026mu;l of 100% ethanol was added into the lysate and vortex briefly. Load the lysate/ethanol mixture onto a Micro Filter Cartridge Assembly to pull down RNA on the filter. Then, centrifuge for 30 sec at 12, 000g. After washed by Wash Solution 1 and 2/3, apply 10\u0026mu;l of Elution Solution (preheated to 75\u0026deg;C) to elute RNA.\u0026nbsp;The extracted total RNA was used to synthesize cDNA using RT Master Mix (TaKaRa, RR036). RT-qPCR was performed using the SYBR-Green qPCR Master Mix (TaKaRa, RR420) on the LightCycler 480 System. Gene expression values were normalized and are shown as a relative fold change compared to the control samples. All experiments were conducted in biological triplicates. And all RT-qPCR primers are listed in Key table for qPCR primers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlasmid construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe plasmids constructed for luciferase assay were referred to the previous protocol \u003csup\u003e65\u003c/sup\u003e. Briefly, the segments of HK1 promoter region were amplified from rat genomic DNA. The HK1 promoter segments were cloned into PGL3_basic plasmid (Promega, Cat# E1751) using restriction enzymes Xho I and Hind III. For mutation of the binding sites, Site-Directed Mutagenesis Kit (Agilent Technologies, #200519) was applied to generation mutation sites. The primer sequences are listed in Key table for qPCR primers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFluorescence-Activated Cell Sorting (FACS) for GFAP+ astrocyte isolation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnimals were perfused with 0.9% Sodium chloride (Sigma, S7653), and L3-6 left dorsal spinal cord tissue was collected on ice and rapidly chopped into small pieces using a sharp scalpel. Then, transferring the tissues into 15-ml Falcon tubes with 3 ml of Trypsin-EDTA (Sigma, T4049) digestion solution and add 6ml (30U) DNase I (Roche, 10104159001, 5U/ml) and incubated for 15 to 20 min at 37\u0026deg;C to dissociate tissue into single-cell suspension. During this step, 200ml pipette was used to blow the suspension up and down every 5 min. \u0026nbsp;Then, 70-mm cell strainer was used to filter the final cell suspension, and 5 ml of ice-cold Hanks\u0026rsquo; balanced salt solution (HBSS) (Thermo Fisher Scientific, 24020117) was applied to wash the strainer. The suspension was collected in a 50-ml Falcon tube and centrifuged at 450g at 4\u0026deg;C for 5 min. Supernatant containing dead cells and debris was discarded, and pellet was resuspended in 2 ml of ice-cold HBSS and centrifuge at 750g at 4\u0026deg;C for 5 min to wash it once. Discard the supernatant and resuspend the pellet in 1ml 30% Percoll (GE Healthcare, 45-001-748) [100% Percoll = 9 parts Percoll + 1 part 10\u0026times; HBSS, Thermo Fisher Scientific, #14185052]. Tubes were spun at 800g for 15 min at 4\u0026deg;C, and pellet was collected in a new 15-ml tube and resuspended in 1 ml of FACS buffer [1X PBS (Gibco, 70013032) + 0.4% BSA (Sigma, A7638) or 1X PBS, 0.5% BSA, 2mM EDTA, 20mM Glucose] to wash once. Then, the cell pellet was resuspended in 300ul of FACS buffer with 1:50 APC anti-GFAP antibody (Thermo Fisher Scientific, #50-9892-82) and incubated on ice with rotated slightly for 1h. Cells were washed in 1ml FACS buffer, pelleted at 750g for 5min and resuspended in FACS buffer containing 4\u0026prime;,6-diamidino-2-phenylindole (DAPI). After staining with DAPI (Sigma, D9542, 1mg/ml in sterile H\u003csub\u003e2\u003c/sub\u003eO, 1:1,000 with sterile ice-cold 1X PBS) on ice for 8min, washed once and resuspended in 0.5ml FACS buffer to sort target cells using the BD FACSAria\u003csup\u003eTM\u003c/sup\u003e Fusion Cell Sorter. Cells were collected into FACS tube with 0.5ml FACS buffer. The fcs files were further analyzed using FlowJo software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell fraction extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL3-6 segments SDH were harvested on day 7 after SNI, with SHAM as control, and homogenized using a Dounce homogenizer in the appropriate volume of CER I (provided by Nuclear and Cytoplasmic Extraction Reagents, Thermofisher Scientific, #78833). After vortexing vigorously and incubating on ice for 10 mins, CER II was added, incubating on ice for 1 min. Then centrifuging the tube for 5 mins at maximum speed and transferring the supernatant, in which containing the \u0026nbsp; cytoplasmic fraction. The insoluble fraction was further suspended by ice-cold NER and the supernatant of lysate containing the nuclear extract. The extracted protein from cytoplasm and nuclei were performed SDS-PAGE gel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual Luciferase Reporter Gene Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe luciferase assay was performed by referring previously described method \u003csup\u003e66\u003c/sup\u003e. In brief, after harvesting the treated hiPSC-derived astrocytes, cell lysis buffer provided by the kit (Beyotime, RG027) was used to lysis cells and the supernatant for further assay. After the buffers reached to room temperature, samples were added to firefly luciferase assay reagent and measure the relative light unit (RLU) at 560nm, using CLARIOstar Plus (BMG LABTECH), \u0026nbsp;located in the CPOS, HKU. Then, the addition of Renilla luciferase assay working buffer quenches the luminescence from the firefly reaction and only obtains the luminescent signal from Renilla reaction at 465nm. Finally, calculating the ratio of luminescence from the experimental reporter to luminescence from the control reporter, with Renilla luciferase as an internal reference to eliminate variations induced by differences in cell number or transfection efficiency.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted Metabolomics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL3-6 segments SDH were harvested on day 7 after SNI, with SHAM as control, and putted in liquid nitrogen. The tissue was ground into power using the Dounce homogenizer in the liquid nitrogen to keep samples frozen. 35mg sample per treatment was submitted to HKU proteomics and metabolomics core for analysing the metabolites in the glycolysis, TCA and PPP pathway. At lease replicants per treatment were performed and error bar was calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChromatin Immunoprecipitation and Quantitative Polymerase Chain Reaction (CHIP-qPCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe previous protocol was referred to examine the protein-DNA interaction \u003csup\u003e67\u003c/sup\u003e. The segments of L3-6 SDH was cut into small pieces and dissociated into single cells using enzyme provided by Neural Tissue Dissociation Kits (Miltenyi Biotec, 130-092-628). Cells then was cross-linked by formaldehyde of final concentration 1%, incubating at RT for 10 mins with slightly vertexing, and quenched by glycine at RT for 5 mins. After washed twice using PBS buffer (contain protein inhibitor), cell membranes were dissolved with the membrane lysis solutions (Pierce\u0026trade; Magnetic ChIP Kit, ThermoFisher Scientific, #26157) to isolate nuclear fraction. Sonication (BioruptorPico UltraSonication System, Diagenode) at 4\u0026deg;C for 30 s with a 30-s pulse was applied to shear genomic DNA into chromatin fragment size range from 200 to \u0026gt;700 bp. 10% of supernatant after centrifugation was was kept as the input and the remaining 90% was used for immunoprecipitation with 5 \u0026mu;g anti-SOX9 antibody (rabbit, Merck Millipore, AB5535), anti-p-Sox9 (rabbit, Abcam, ab59252) or normal rabbit IgG control overnight at 4\u0026deg;C. Followingly, the protein-DNA complex was isolated using 20 \u0026mu;L magnetic beads. The purified DNA served as the templates for the qPCR analysis using primers flanking the binding motifs on the \u003cem\u003eHK1\u0026nbsp;\u003c/em\u003epromoter region. The ChIP- qPCR primers used are listed in Table xx.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDead cell removal and cell preparation for single-cell RNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protocol for the sample preparation for scRNA-seq is referring the previous published article \u003csup\u003e68\u003c/sup\u003e. Animals were perfused using 0.9% saline, and the dorsal horn on the left of the L3-6 spinal cord was harvested in ice-cold Hanks\u0026rsquo; balanced salt solution (HBSS) (Thermo Fisher Scientific, 14175095) on ice and chopped into small pieces using a sharp scalpel. We use the modified papain digestion protocol to achieve single-cell suspension [Miltenyi Neural Tissue Dissociation Kit (P) 130-092-628]. In details, tissue was transferred into 15-ml Falcon tubes containing 2 ml of digestion solution, and incubated at 37\u0026deg;C for 10 to 15 mins. During the dissection period, the 200ml pipette was used to blow the suspension up and down every 5 min. The dissected cell suspension was passed through a 70-mm cell strainer, and 5 ml of HBSS (with Ca and Mg; Thermo Fisher Scientific, 24020117) was applied to wash the strainer. The suspension was collected in a 15-ml Falcon tube and centrifuged at 450g at 4\u0026deg;C for 5 min. The pellet was resuspended in 1ml 30% Percoll (GE Healthcare, 45-001-748) [9 parts Percoll + 1 part 10\u0026times; HBSS (Sigma-Aldrich, H4385) = 100% Pecoll; 3 parts 100% Pecoll + 7 parts 1\u0026times; HBSS = 30% Pecoll], and discarded the supernatant in which containing dead cells and debris. Tubes were spun at 800g for 15 min at 4\u0026deg;C, and pellet was collected in a new 15-ml tube and resuspended in 0.5 ml of HBSS buffer (1\u0026times; HBSS + 0.4% BSA). Red blood cells (RBCs) were lysed by incubating cells with RBC lysis \u0026nbsp;buffer \u0026nbsp; (BioLegend, \u0026nbsp;420301) \u0026nbsp;for \u0026nbsp; 15 \u0026nbsp;min \u0026nbsp;at \u0026nbsp; room \u0026nbsp;temperature; \u0026nbsp;cells \u0026nbsp; were \u0026nbsp;washed \u0026nbsp;and \u0026nbsp; resuspended in HBSS buffer. All steps were performed at 4\u0026deg;C. After FACS and collected DAPI negative cells, cells were counted using an automated cell counter (Thermo Fisher Scientific Countess, AMQAX1000), live/dead measures were made using trypan blue (Gibco, 15250061), and samples with a viability of higher than 70% were used for downstream scRNA-seq analysis. scRNA-seq was performed using the Chromium platform (10X Genomics, CPOS, HKU) with a 3\u0026prime; gene expression V3 kit and an iNePut of ~10,000 viable cells from a debris-free suspension. The steps of Library construction and QC, NGS sequencing, and primary analysis were completed in CPOS, and the files outputted from the \u0026lsquo;cellranger count\u0026rsquo; and \u0026lsquo;multi\u0026rsquo; pipelines were collected for further analysis. Downstream analyses, such as graph-based clustering and differential expression analysis/visualization, were performed using the R studio and the Seurat package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-cell RNA sequencing and quality-control filtering\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle cells in each sample were encapsulated into droplet emulsions and converted to barcoded single-cell cDNA libraries using the Chromium Single Cell 3\u0026rsquo; V2 Li- brary, Gel Bead, Chip, and Multiplex Kit (10x Genomics), following the manufacturer\u0026rsquo;s guidelines. The isolated single cells were then loaded in each channel, targeting for a total of 10,000 cells per library. Single-cell libraries were then sequenced on a NovaSeq 6000 System (Illumina). The sequenced reads were then mapped to the rat genome (NCBI Rnor6.0) using the 10x Genomics Cell Ranger (v2.1.1) pipeline to generate the filtered gene-barcode matrix containing valid cell barcodes and transcript unique molecular identifier (UMI) counts. For each gene and each cell barcode, UMIs were counted to construct digital expression matrices, which were filtered a second time using Seurat software. Genes found in fewer than three cells and cells with \u0026lt; 200 genes having nonzero counts were excluded from the analysis. We also removed cells with total UMI counts \u0026gt;7,500 or the number of detected genes was \u0026gt;2,500 in order to exclude possible multiple captures, a key problem in microdroplet-based tests. We further eliminated low-quality cells where more than 4% of the counts belonged to mitochondrial genes after visually examining the distribution of cells by the fraction of expressed mitochondrial genes. These QC standards were used, and 49, 571 single cells were used in the subsequent investigations. To get the normalized count, the filtered matrix was subjected to library size normalization in Seurat.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple scRNA-seq dataset integration and t-SNE analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to compare cell kinds and proportions under the three conditions, the dataset integration methodology was based on the previously published method \u003csup\u003e69\u003c/sup\u003e. Several different scRNA-seq datasets were combined into an integrated, unbatched dataset using the Seurat software (v.4.1.0). In summary, as previously mentioned, 2000 features were shown to have significant cell-to-cell variance. Use of the FindIntegrationAnchors function allowed for the identification of anchors between individual datasets. By entering these anchors into the IntegrateData function, all cells\u0026apos; batch-corrected expression matrices were produced, enabling the integration and analysis of cells from various datasets.\u003c/p\u003e\n\u003cp\u003eCell Ranger employs Principal Components Analysis (PCA) to alter the dimensionality of the dataset from cells x genes to cells x M, where M is a user-selectable number of principle components, in order to reduce the gene expression matrix to its most significant properties. Cell Ranger passes the PCA-reduced data into t-Stochastic Neighbor Embedding (t-SNE) in order to visualize the data in two dimensions.\u003c/p\u003e\n\u003cp\u003eThe cells clustered together based on shared features after non-linear dimensional reduction and the projection of all cells into two-dimensional space by t-SNE; markers for each cluster that were identified were sought using Seurat\u0026apos;s FindAllMarkers function. The expression of the canonical markers of specific cell types was used to classify and annotate the clusters based on published research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferential expression genes (DEGs) analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith the following parameters, we used Seurat\u0026apos;s \u0026quot;FindAllMarkers\u0026quot; tool to find genes that express themselves differently between clusters: min.pct = 0.1, logfc.threshold = 0.25, pseudocount.use = 0.1, only.pos = T. The p-values for comparisons and the adjusted p-values, depending on Bonferroni correction, for each gene in the dataset were obtained using the non-parametric Wilcoxon rank-sum test. The log-transformed and scaled DEGs based on gene expression were shown using a heatmap.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO Biological progress (GOBP) analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the DEGs was identified between the treatments, the Enricher database (\u003cu\u003ehttps://maayanlab.cloud/Enrichr/\u003c/u\u003e) was applied to GO enrichment analysis for the biological progress. GO terms with a p value \u0026lt; 0.05 were significant the highly associated GO terms of biological process were shown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKEGG pathway analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSimilar to the GOBP analysis, DEGs identified in the compared treatments was applied to KEGG enrichment analysis using the KOBAS database (\u003cu\u003ehttp://kobas.cbi.pku.edu.cn/\u003c/u\u003e). KEGG with a p value \u0026lt; 0.05 were significant the highly associated pathways were shown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePseudotime trajectory analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle-cell pseudotime trajectory analysis was performed with monocle3 \u003csup\u003e70\u003c/sup\u003e (\u003cu\u003ehttps://cole-trapnell-lab.github.io/monocle3/docs/trajectories/\u003c/u\u003e). The developmental processes of cell differentiation were inferred using Monocle 3. These algorithms use an individual cell\u0026apos;s asynchronous evolution within an unsupervised framework to position the cells along a trajectory matching to a biological process. This increases the temporal resolution of transcriptome dynamics of key regulatory factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCUT\u0026amp;Tag analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we employed the CUT\u0026amp;Tag (Cleavage Under Targets and Tagmentation) technology to map protein-DNA interactions and histone modifications in native chromatin. The protocol begins with cell preparation and fixation to preserve chromatin integrity. Specific antibodies bind to the target proteins or histone modifications, followed by the addition of a transposase adaptor complex, which performs targeted tagmentation. This process cleaves the DNA at antibody-bound sites and inserts sequencing adapters simultaneously. The resulting DNA fragments are then extracted, amplified, and purified to create a sequencing library by the PTM BIO company. The obtained sequencing results were analyzed by using the R studio and IGV.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHexokinase activity assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor measuring the activity of hexokinase, the hexokinase activity assay kit (Abcam, ab136957) has been utilized according to the manufacturer\u0026rsquo;s instructions. In short, the harvest of cultured human astrocytes or the FAC-sorted GFAP+ astrocytes from rat dorsal spinal cord for at least 1 x 10\u003csup\u003e6\u003c/sup\u003e cells. The cell number can be further measured by CyQUANT cell proliferation assay kit (Invitrogen, C7026). Ice-cold assay buffer was used to lysis cells and then centrifuge at 12,000 rpm for 5 mins at 4\u0026deg;C to remove the insoluble materials. The supernatant was transferred into new tube, keeping on ice. For measurement, the reaction buffer and cell lysis were added into the 96-well plate and incubated for 20-60 mins at RT, followed the protocol provided by the product. Finally, measuring OD 450nm for calculation and following analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLactate and pyruvate accumulation measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the determination of lactate and pyruvate levels in the human astrocytes and sorted GFAP\u003csup\u003e+\u003c/sup\u003e astrocyte cells from rat dorsal spinal cord after different treatments both of the SNI operation and the AAV infections by intraspinal injection. L-lactate assay kit (Sigma, MAK329) was utilized according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistics analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll results are expressed as mean \u0026plusmn; SEM. For comparison between two groups, two-tailed paired\u003cem\u003e\u0026nbsp;t-test\u0026nbsp;\u003c/em\u003ewas used at a designed significance level of \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. For the measurements taken at different time points were compared using one-way ANOVA followed by Turkey\u0026rsquo;s multiple comparisons or two-way repeated-measures ANOVA followed by Sidak\u0026apos;s multiple comparison. *, \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. Statistical analyses were performed using GraphPad Prism 9.3.0. The statistical details of each experiment can be found in the figure legends.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Centre for PanorOmic Sciences of The University of Hong Kong for RNA sequencing and metabolomics services, as well as the imaging Core facility of the Neuroscience department at the City University of Hong Kong. This work was supported by General research funding from Hong Kong UGC (17107822), Health and Medical Research Fund (09201846), University Start-up grant (9610588) and funding from Peter Hung Professorship in Pain Research granted to Professor Cheung Chi Wai.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.A.L., Y.C., and M.C contributed to the conception and design of the study; Y.C., A.W., C.F., and D.Z contributed to the acquisition and analysis of data; Y.C., H.C., and Y.L. performed the bioinformatics analyses for scRNA-Seq. Z.M., and Y.C. performed the bioinformatics analyses for CUT\u0026amp;Tag. J.A.L., C.W.C., and S.W.provided resources and funding. J.A.L., Y.C., and M.C., analyzed and interpreted the data. Y.C., A.W., C.F., J.A.L., and Y.L prepare the figures. Y.C., J.A.L., and M.C., co-wrote the manuscript with critical input from all authors\u003cem\u003e.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edata\u0026nbsp;\u003c/strong\u003eFigures S1 and Table S1, related to Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edata\u0026nbsp;\u003c/strong\u003eFigure S2 and S3, related to Figure 8.\u003c/p\u003e\n\u003cp\u003eTable S2, related to Figure 4.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eColloca, L.\u003cem\u003e, et al.\u003c/em\u003e Neuropathic pain. \u003cem\u003eNat Rev Dis Primers \u003c/em\u003e\u003cstrong\u003e3\u003c/strong\u003e, 17002 (2017).\u003c/li\u003e\n\u003cli\u003eJi, R.R., Donnelly, C.R. \u0026amp; Nedergaard, M. 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Astrocytes contribute to long-lasting neuroinflammation in the dorsal horn, driving NeP development. Directly targeting astrocytes is not feasible due to their roles in supporting neuronal homeostasis and pain resolution. Despite this understanding, the heterogeneity of astrocytes and the regulation of deleterious subsets emergence in pain remain less known. Through a comprehensive approach involving metabolomic, single-cell transcriptomic, epigenomic profiling and regional astrocyte-specific perturbation studies, we identified distinct astrocyte clusters under physiological and pathological pain conditions, and elucidated mechanisms by which metabolic regulation of neuroinflammatory astrocyte subsets during pain pathogenesis. We found an astrocyte specifier, Sox9, transcriptionally regulates Hexokinase1 (HK1), a critical enzyme that catalyzes the first step in glucose metabolism irreversibly, contributing to astrocytic glycolysis homeostasis. Initial nerve damage induced abnormal phosphorylation of Sox9, triggering aberrantly activation of HK1 for high-rate glycolysis in astrocytes. Moreover, the excessive lactate production from heightened glycolysis remodeled histones of gene promoters via lactylation, H3K9la, promoting transcriptional modules of genes governing pro-inflammatory and neurotoxic signaling, which induced pathogenic astrocyte properties while reducing beneficial populations, ultimately causing persistent pain state. Importantly, we demonstrate that targeted modulation of the SOX9-HK1-H3K9la axis specifically dampens deleterious astrocyte subsets, promoting long-lasting recovery of NeP. Collectively, our findings unveil a novel immunometabolic mechanism and identify multiple potential targets for effective therapeutic interventions in the treatment of NeP.\u003c/p\u003e","manuscriptTitle":"SOX9 regulation of Hexokinase 1 controls neuroinflammatory astrocyte subtypes in neuropathic pain","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-19 14:00:48","doi":"10.21203/rs.3.rs-5916660/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"172aa2be-8d9b-4a10-a72b-7cd4eae4425b","owner":[],"postedDate":"February 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":43953833,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Chronic pain"},{"id":43953834,"name":"Biological sciences/Neuroscience/Glial biology/Astrocyte"}],"tags":[],"updatedAt":"2025-11-22T08:07:52+00:00","versionOfRecord":{"articleIdentity":"rs-5916660","link":"https://doi.org/10.1038/s41467-025-65092-5","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-11-21 05:00:00","publishedOnDateReadable":"November 21st, 2025"},"versionCreatedAt":"2025-02-19 14:00:48","video":"","vorDoi":"10.1038/s41467-025-65092-5","vorDoiUrl":"https://doi.org/10.1038/s41467-025-65092-5","workflowStages":[]},"version":"v1","identity":"rs-5916660","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5916660","identity":"rs-5916660","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}