NRF1/NFE2L1 orchestrates spatiotemporal regulation of protein degradation network in skeletal muscle

NRF1/NFE2L1 orchestrates spatiotemporal regulation of protein degradation network in skeletal muscle | 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 NRF1/NFE2L1 orchestrates spatiotemporal regulation of protein degradation network in skeletal muscle Zhendi Wang, Wei Shen, Rui Zhang, Xirui Yan, Jinzhi Wu, Shengnan Liu, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7736640/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Skeletal muscle (SkM) relies on precise regulation of protein synthesis and degradation for functional integrity, with the ubiquitin-proteasome system (UPS) as a cornerstone of homeostasis. Nuclear factor (erythroid-derived 2)-like 1 (NFE2L1), a conserved CNC-bZIP transcription factor, integrates redox balance and proteasome gene expression, but its fiber-type-specific roles in SkM remain unclear. Here, we integrated multi-omics datasets from aging and sarcopenia cohorts to characterize the spatiotemporal activity of NFE2L1 in SkM. Genetic variants in NFE2L1 were significantly associated with lean muscle mass and grip strength in the UK Biobank. Striated muscle-specific Nfe2l1 knockout mice ( Nfe2l1 (SM)-KO) displayed age-dependent SkM atrophy characterized by preferential loss of Type IIb fibers, heightened inflammatory response, fat infiltration and regulated cell death (RCD). Proteomic, metabolomic, and lipidomic analyses unveiled a NFE2L1-driven regulatory network maintaining UPS function and metabolic homeostasis. Single-nucleus RNA sequencing revealed global UPS dysfunction and shifts in myonuclear states toward RCD-prone phenotypes in Nfe2l1 (SM)-KO muscle. Pharmacological activation of proteasomes with rolipram partially mitigated atrophy in juvenile knockouts, and human aging SkM datasets confirmed conserved myonuclear state transitions. Collectively, NFE2L1 emerges as a pivotal spatiotemporal regulator of SkM proteostasis, bridging UPS maintenance with fiber-type integrity and offering therapeutic targets for age-related muscle decline. Biological sciences/Cell biology/Cell death Biological sciences/Cell biology/Cell signalling NFE2L1 Skeletal muscle Ubiquitin-proteasome system Proteostasis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Significance Statement Skeletal muscle decline during aging is linked to impaired proteostasis and cell death. This study identifies NFE2L1 as a key regulator of the ubiquitin-proteasome system, controlling muscle fiber-type integrity and suppressing regulated cell death. Genetic and pharmacological evidence in mice and humans reveals NFE2L1 maintains proteostasis and metabolic balance, offering a therapeutic target to combat age-related muscle atrophy and functional decline. Introduction Skeletal muscle (SkM), a central hub for movement, postural support, and metabolic balance, is unparalleled in its dynamic regulation of protein synthesis and catabolism, processes fundamental to its structural integrity and functional adaptability( 1 , 2 ). Dysregulation of SkM protein metabolism, which is instigated by aging, denervation, physical inactivity, nutritional stress, or disease, underlies a spectrum of pathological states, most notably SkM atrophy( 3 – 5 ). Maintaining equilibrium in SkM protein turnover is therefore essential for preserving muscle health and functional capacity across the lifespan. Human SkM comprises slow-twitch (Type I) and fast-twitch (Type II) fibers, with Type II further subclassified into IIa and IIx subtypes, each exhibiting distinct profiles of protein synthesis and degradation( 6 ). In mice, SkM also includes Type IIb fibers. The contraction velocity increases in the order of Type I, Type IIa, Type IIx, and Type IIb. Type I fibers, endowed with abundant mitochondria and capillaries, rely on oxidative metabolism to sustain stable protein synthesis, supported by a balanced interplay between autophagy-lysosome and ubiquitin-proteasome systems (UPS) that ensures protein quality control and fiber integrity, making them well-suited for prolonged, low-intensity aerobic activities. With aging, Type I fibers demonstrate relative resilience in maintaining oxidative capacity and fiber morphology( 7 ). In contrast, Type II fibers which is critical for explosive, high-intensity movements exhibit rapid activation of the mechanistic target of rapamycin complex 1 (mTORC1) pathway to enhance protein synthesis in response to exercise, coupled with a highly active UPS that accelerates protein degradation during transient metabolic stress, such as fatigue or energy flux, to fuel contraction( 7 , 8 ). This plasticity renders Type II fibers more susceptible to post-exercise protein loss. Aging exacerbates Type II fiber vulnerability, driving selective atrophy of IIx/IIb subtypes, blunting anabolic responsiveness, and skewing fiber composition toward a higher Type I proportion, a shift linked to neuromuscular, hormonal, and inflammatory perturbations in fiber-specific protein turnover. Dysfunction of the UPS in SkM fibers leads to accumulation of damaged proteins, forming aggregates that induce stress responses and disrupt cellular homeostasis( 4 , 9 ). Severe stress triggers regulated cell death (RCD), such as apoptosis, necroptosis, pyroptosis and panoptosis, culminating in fiber loss, reduced muscle mass, and strength decline( 10 ). UPS impairment also compromises muscle stem cell function, hindering regenerative capacity( 11 ). Given the inherently higher UPS activity in Type II fibers, these subtypes are particularly sensitive to UPS deficiency or dysfunction. Nuclear factor (erythroid-derived 2)-like 1 (NFE2L1/NRF1), a conserved CNC-bZIP transcription factor, acts as a master regulator of proteasome homeostasis, integrating redox balance with proteasome subunit gene expression( 12 , 13 ). Under basal conditions, NFE2L1 maintains low protein abundance via post-translational regulation while driving constitutive transcription of proteasome subunits to sustain basal proteasome activity. Upon cellular stress, including oxidative, endoplasmic reticulum (ER), and proteotoxic stress, activated NFE2L1 translocates to the nucleus, where it binds antioxidant response elements (AREs) in proteasome subunit promoters to upregulate gene expression and enhance damaged protein clearance( 14 , 15 ). Its regulatory output is further refined by alternative splicing and dynamic post-translational modifications, including glycosylation, phosphorylation, and ubiquitination, which modulate its stability, nuclear localization, and DNA-binding affinity to fine-tune proteasome biogenesis and cellular stress resilience( 14 , 15 ). Although previous investigations have firmly established the UPS as a fundamental pillar of SkM homeostasis and implicated NFE2L1 in proteasome regulation, the fiber-type-specific functions of NFE2L1 within SkM remain largely unexplored. In this study, we comprehensively integrated publicly available chromatin immunoprecipitation sequencing (ChIP-Seq) and transcriptome datasets from aging and sarcopenia cohorts, aiming to elucidate the spatiotemporal patterns of NFE2L1 expression and transcriptional activity in SkM. By leveraging the extensive UK Biobank cohort, we successfully identified genetic variants in NFE2L1 that were significantly associated with lean muscle mass and grip strength. Using striated muscle-specific Nfe2l1 -knockout mice ( Nfe2l1 (SM)-KO), we provided robust evidence of Nfe2l1 deficiency-induced and age-dependent progressive SkM atrophy. This atrophy was characterized by the preferential loss of Type IIb fibers, activation of regulated cell death (RCD) pathways, chronic inflammation, and fibrotic changes. Through proteomics, untargeted metabolomics, and lipidomics, we further delineated a NFE2L1-driven regulatory network in SkM, thereby highlighting its pivotal role in maintaining UPS function and regulating downstream metabolic pathways. Single-nucleus RNA sequencing (snRNA-Seq) revealed a global decline in UPS function and elevated cellular stress across various myonuclei subtypes in Nfe2l1 (SM)-KO muscle. Notably, this was accompanied by the depletion of a myonuclear state characterized by high UPS activity and a pronounced shift toward RCD-susceptible states. Moreover, pharmacological intervention with rolipram, a selective activator of the cAMP-PKA pathway that enhances proteasome function, partially reversed these pathological phenotypes in juvenile Nfe2l1 (SM)-KO mice. Analyses of human aging SkM datasets further validated our findings, underscoring the conserved nature of myonuclear state transitions during SkM senescence. Collectively, our results firmly establish NFE2L1 as a critical spatiotemporal regulator of proteostasis in SkM, offering novel insights into the mechanisms underlying aging-related muscle decline and paving the way for potential therapeutic interventions. Results The associations of NFE2L1 with SkM mass and function in humans. To elucidate the pivotal role of NFE2L1 in SkM, we conducted an in-depth analysis of the mRNA abundance of 1,839 human transcription factors (TFs) using the Genotype-Tissue Expression (GTEx) dataset( 16 ), which encompassed 263 male and 146 female subjects. Notably, NFE2L1 emerged as one of the top-ranking TFs in SkM, securing the fourth position among the most enriched TFs (Fig. 1 A). Further exploration revealed that, when compared to other tissues, SkM exhibited the highest NFE2L1 mRNA levels (Supplementary Fig. S1 ), emphasizing its tissue-specific prominence. In addition, among the 10 most highly expressed TFs in SkM, NFE2L1 stood out uniquely, as it was the only factor demonstrating an age-dependent decline trend (Fig. 1 B). In addition, the trend analyses conducted separately for male and female cohorts (Fig. 1 C and Supplementary Fig. S2A and Table S1 ) provided robust validation of this age-related decrease, indicating a potential role of NFE2L1 in age-associated SkM changes. To comprehensively define the regulatory network of NFE2L1 in SkM, we computed the Pearson correlation coefficient between NFE2L1 and all other genes within SkM samples. Genes were meticulously selected based on stringent criteria: those with a correlation coefficient R > 0.5 and P < 0.05. This process yielded a total of 1,465 genes that were co-expressed with NFE2L1 . Among these, notable gene categories included proteasome subunit genes, such as PSMD7 , PSMD2 , PSMD11 , PSMB5 , PSMD3 , and PSMD1 , as well as antioxidant-related genes, such as SQSTM1 , ME1 , GSR , SOD1 , GCLC , and SOD2 (Supplementary Fig. S2B-C). In addition, we performed an enrichment analysis on the co-expressed genes using the human C3 gene sets from the Molecular Signatures Database (MSigDB)( 17 ). This analysis led to the identification of the term "NFE2L1_TARGET_GENE," which includes 253 potential target genes of NFE2L1 (Fig. 1 D and SI Appendix, Table S2). Leveraging the STRING( 18 ) website for protein-protein interaction analysis and visualizing the results with Cytoscape, we determined that the UPS was the most prominent network (Supplementary Fig. S2D). Additionally, KEGG enrichment analysis of the 1,465 co-expressed genes highlighted the proteasome pathway and ubiquitin-mediated protein degradation as the most significant biological processes (Fig. 1 E). Furthermore, we analyzed the GSE167186 dataset, which comprised 19 young healthy subjects, 29 older healthy subjects, and 24 sarcopenia patients (Supplementary Fig. S2E). Our analysis revealed a significant decreasing trend in NFE2L1 expression (Fig. 1 F). Through differential expression analysis (DEA), we further identified a notable reduction in the expression levels of numerous proteasome subunit genes (Supplementary Fig. S2F and Table S3 and S4). To validate our findings, we explored another public dataset, GSE175495. Consistent with our previous results, we observed that the expression of NFE2L1 was significantly lower in the older group (n = 11) compared to the younger group (n = 12) (Supplementary Fig. S3A). Subsequently, we conducted an enrichment analysis on the 314 genes co-expressed with NFE2L1 . The analysis highlighted that the most significant terms were "NFE2L1_TARGET_GENE" (Supplementary Fig. S3B) and biological processes related to the UPS (Supplementary Fig. S3C). Moreover, a substantial number of proteasome subunit genes exhibited significantly decreased mRNA expression in the aged group (Supplementary Fig. S3D). To investigate the expression patterns of NFE2L1 in fast-twitch and slow-twitch muscle fibers, we further analyzed the public dataset GSE200398. This dataset includes 11 samples with a high percentage of fast-twitch fibers (defined as the Fast group) and 12 samples with a low percentage of fast-twitch fibers (defined as the Slow group) (Supplementary Fig. S4A-D). The results showed that the expression levels of NFE2L1 and proteasome subunit genes were significantly higher in the Fast group than those in the Slow group (Fig. 1 G). In addition, correlation analysis within groups revealed that, in the Fast group, NFE2L1 expression was significantly positively correlated with the percentage of fast-twitch fibers (Fig. 1 H), whereas no significant correlation was observed in the Slow group. These findings collectively highlight the important role of NFE2L1 in regulating UPS homeostasis in SkM, as well as its potential involvement in age-related skeletal muscle alterations. To dig deeper into the relationship between NFE2L1 and SkM mass and function, we carried out a candidate gene association study (CGAS) utilizing the extensive UK Biobank (UKB)( 19 ) cohort. Our analysis encompassed a vast sample size: 367,942 participants (197,749 females and 170,193 males) for hand grip strength (HGS) assessment and 353,086 participants (189,591 females and 163,495 males) for appendicular lean mass (ALM) evaluation. Applying a highly stringent significance threshold of 1.04×10⁻⁴, we detected significant associations for all the studied traits. Specifically, 14 variants were found to be linked with ALM, while 6 variants were associated with HGS. Following the exclusion of non-replicated variants across genders, 13 variants remained associated with ALM and 6 with HGS (Fig. 1 I and Supplementary Fig. S5 and Table S5-6). Notably, several of these associations achieved genome-wide significance (α = 5.0×10⁻⁸), providing compelling evidence that NFE2L1 may play a crucial and fundamental role in human SkM biology, potentially influencing both muscle mass and functional capacity. Generation and phenotypic characterization of striated muscle-specific Nfe2l1 knockout mice. To characterize the function of NFE2L1 in SkM, we generated Nfe2l1 (SM)-KO (KO) mice by crossing Nfe2l1 fl/fl (Flox) mice with Ckm -Cre +/- mice (Cre). Quantitative analysis revealed a 61.6% reduction in Nfe2l1 mRNA expression in SkM of KO mice compared to littermate Flox controls, with no significant changes in liver expression, confirming muscle-specific gene ablation (Supplementary Fig. S6A). Immunoblotting using a pan-NFE2L1 antibody detected diminished protein isoforms (25–140 kDa) in KO SkM relative to Flox littermates (Supplementary Fig. S6B), validating successful generation of the KO model for functional studies. Male KO mice exhibited significant reductions in body weight gain (Fig. 2 A), lean mass (Supplementary Fig. S7A), and SkM mass (Fig. 2 B–C and Supplementary Fig. S9), accompanied by increased fat mass (Supplementary Fig. S7B), compared to control littermates. Functional assessments in 20-week-old male KO mice revealed profound declines in athletic performance. The grip strength of KO mice was reduced by 17.3% (Supplementary Fig. S8A), hanging time during rotarod testing decreased by 61.8% (Supplementary Fig. S8C), and the number of stopped moving (measured by shock events) during the running wheel test was doubled compared to Flox controls (Supplementary Fig. S8B), indicating compromised motor coordination and endurance. Histopathological analysis by H&E staining showed no significant genotype-specific differences in quadriceps muscles at 4 weeks of age (Fig. 2 D and SI Appendix Fig. S10). By 20 weeks, KO mice exhibited striking alterations, including myocyte size heterogeneity, ectopic nuclear localization in the cytoplasm, cytoplasmic structural disintegration with indistinct boundaries, and increased aggregates of inflammatory cells and adipocyte infiltration (Fig. 2 D and SI Appendix Fig. S11 A-D). At 50 weeks, muscle pathology worsened, characterized by severe muscle fiber atrophy and loss, along with heightened inflammatory cell and adipocyte infiltration (Fig. 2 D and SI Appendix Fig. S12). These changes were not limited to quadriceps but also observed in gastrocnemius and triceps brachii muscles (SI Appendix Fig. S13), and identical phenotypic alterations were recapitulated in female KO mice (SI Appendix Fig. S14 A-I). To investigate the molecular basis of these phenotypes, RNA-seq was performed on SkM tissues from 20-week-old KO and Flox mice, identifying 586 significantly downregulated genes (e.g., proteasome subunit genes Psmd1 , Psmd3 , Psmc2 ) and 1,066 upregulated genes (e.g., inflammatory response gene Cx3cl1 and apoptosis-related genes Tlr4 , Casp3 ) (Supplementary Fig. S16A-C). Gene set enrichment analysis (GSEA) confirmed significant downregulation of the proteasome pathway and upregulation of chemokine signaling associated with inflammation (Fig. 2 E). RT-qPCR validation revealed marked upregulation of macrophage markers ( Adgre1 , Cd68 ), pyroptosis-related genes ( Casp1 , Nlrp3 , Pycard ) in KO mice (Fig. 2 F). Immunohistochemical staining for apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), which is also known as target of methylation-induced silencing (TMS1), and F4/80 (macrophages), along with Oil-Red O staining, demonstrated increased inflammation, RCD and intramuscular fat infiltration in KO muscle tissues compared to Flox controls (Fig. 2 G and SI Appendix Fig. S15 A-C, S17 A-B). To explore fiber type-specific effects of Nfe2l1 deficiency, we analyzed expression of muscle fiber marker genes including Myh4 (Type IIb), Myh2 (Type IIa), and Myh7 (Type I). RNA-seq data analysis showed decreased Myh4 expression and increased Myh2 / Myh7 levels in KO SkM (Fig. 2 J). Immunofluorescence staining in calf triceps muscle confirmed a 57.6% reduction in Type IIb fibers (MYH4 + ), while the proportion of Type I fibers (MYH7 + ) was significantly increased, and a trend toward increased Type IIa fibers (MYH2 + ) in KO mice compared to controls (Fig. 2 H–I and SI Appendix Fig. S18). These findings indicate that Nfe2l1 deficiency drives selective loss of Type IIb fibers and a phenotypic shift toward Type IIa and Type I fiber populations in KO mice by 20 weeks of age. Early-onset molecular and ultrastructural dysregulation in 4-week-old KO SkM without overt pathological phenotypes. The earlier pathological findings (Fig. 2 D and SI Appendix Fig. S10) indicated minimal impact on the SkM of 4-week-old KO mice. To further validate the effect of Nfe2l1 deletion at this age, we collected muscle tissues (Supplementary Fig. S19) and analyzed organ coefficients (Fig. 3 A), observing no significant differences between genotypes. Consistent with the 20-week-old cohort, analyses of inflammation-related markers (Supplementary Fig. S20) in SkM tissues revealed no significant changes in 4-week-old KO mice, suggesting that Nfe2l1 deletion did not induce notable muscle pathologies at this early stage. Immunofluorescence staining also showed no alterations in muscle fiber type composition (Supplementary Fig. S21). Despite the absence of overt pathological phenotypes, ultrastructural analysis of quadriceps muscles unveiled striking subcellular abnormalities (Fig. 3 B). In KO mice, sarcomere structures were damaged, with blurred cross-striations, twisted or fragmented Z lines (or even Z-line loss), and disorganized myofilament arrangement. Mitochondria exhibited significantly increased cristae density but disordered organization, often forming concentric or fingerprint-like aggregates, hallmarks of chronic energy stress. Additionally, outer mitochondrial membrane rupture with content release and marked dilation of the sarcoplasmic reticulum lumen into vesicular or balloon-like structures, accompanied by myofibril hyperextension, were observed. These ultrastructural defects suggest early-onset dysfunction in contractile and bioenergetic machinery. Differential proteomic analysis of calf muscles identified 39 significantly downregulated, 182 upregulated, and 1,656 unchanged proteins in KO mice (Supplementary Fig. S22A). GSEA revealed significant suppression of the proteasome, KEAP1-NFE2L2 axis, and organic acid catabolic pathways in the KO muscle, while upregulated pathways were enriched in cell stress responses, including antigen processing/presentation (APP), HSF1-mediated heat shock response (HSR), oxidative stress-induced senescence, and apoptosis (Fig. 3 C). Downregulated proteins were predominantly associated with the UPS, including proteasome subunits (ADRM1, PSMA1)( 20 ), NPL4 homolog, ubiquitin recognition factor (NPLOC4) and NSFL1 (p97) cofactor (p47) (NSFL1C)( 21 ) (Fig. 3 D and SI Appendix Fig. S22B). Upregulated proteins were linked to ER stress ( 22 ), apoptosis ( 23 ), and cellular senescence (Fig. 3 D and SI Appendix Fig. S22C), indicating a coordinated stress response to UPS dysfunction. Untargeted metabolomics further revealed metabolic dysregulation in KO muscle. Orthogonal partial least squares discriminant analysis (OPLS-DA) distinguished metabolic profiles between Flox and KO groups (Supplementary Fig. S22D), with metabolite set enrichment analysis (MSEA) identifying six altered pathways: gluconeogenesis, lactose degradation, sphingolipid metabolism, glucose–alanine cycle, pyruvate metabolism, and glycerolipid metabolism (Fig. 3 E–F and SI Appendix Fig. S22E–F). Levels of malic acid and alanine were significantly elevated, while MG(0:0/16:0) and D-glucose were reduced in KO mice. Targeted lipidomics confirmed a reduction in monohexosylceramide (Hex1Cer), a sphingolipid critical for membrane integrity/signaling( 24 ) as well as increase in glycerolipids (triglycerides [TG], diacylglycerols [DG]) in KO mice (Fig. 3 G and SI Appendix Figs. S22G–I), suggesting impaired lipolysis consistent with NFE2L1’s role in regulating adipocyte lipolytic enzymes( 25 ). Unveiling the cellular and molecular landscape of 4-week-old Nfe2l1 (SM)-KO mice via snRNA-seq. To achieve high-resolution characterization and further validate the cellular and molecular mechanisms underlying early-stage (4-week-old) SkM structural and metabolic alterations in Nfe2l1 (SM)-KO mice, we performed snRNA-seq on calf muscle tissue. Dimensionality reduction and clustering analysis identified 24 distinct cell clusters (labeled 0–23, Supplementary Fig. S23). Based on marker gene analysis, we identified 12 major nuclear populations that encompassed all typical cell types found in SkM tissue (Fig. 4 A-B and Supplementary Fig. S24A-L, Table S9). These included five types of multinucleated myofiber nuclei, namely type I ( Myh7 ), IIa ( Myh2 ), IIx ( Myh1 ), IIb ( Myh4 ), and myotendinous junction fibers (MTJ, Col22a1 ), as well as seven mononuclear cell types, including adipogenic progenitor cells (APC, Apod ), endothelial cells (EC, Pecam1 ), fibro-adipogenic progenitors (FAP, Dcn ), immune cells (IC, Ptprc ), satellite cells (SC, Pax7 ), smooth muscle cells (SMC, Myh11 ), and tenocytes (Teno, Mkx )( 26 , 27 ). Using Single-Cell rEgulatory Network Inference and Clustering (SCENIC)( 28 ), we identified five relatively specific regulons for these 12 nuclear types, further confirming the accuracy of our cell type annotation (Supplementary Fig. S24M). For example, the activity scores of ESRRG(+) and PPARGC1A(+), key regulators of mitochondrial biogenesis and function( 29 , 30 ), were higher in type I, IIa, and IIx myonuclei than in other nuclear types, such as IIb, MTJ, and non-myonuclei (Supplementary Fig. S24M). Nuclear composition analysis showed that type IIb myonuclei were predominant in both Flox and KO groups, accounting for 61.71% and 61.75%, respectively (Fig. 4 A, right panel). Notably, in the KO mice, the proportions of FAP and IC were increased, suggesting that early muscle fiber damage may induce IC aggregation and abnormal proliferation of FAP( 31 ). We next performed DEA between Flox and KO groups for all five myonuclear types and then focused on the three main myonuclear populations (IIb, IIx, and IIa), since MTJ and type I comprised a small fraction and showed few differentially expressed genes (DEGs) (Fig. 4 C and Supplementary Fig. S25A). Venn analysis of downregulated and upregulated genes in IIb, IIx, and IIa myonuclei revealed the presence of overlapping downregulated and upregulated genes, with greater overlap among upregulated genes (Supplementary Fig. S25B-C). Functional enrichment analysis of downregulated genes demonstrated that IIb myonuclei were mainly enriched in the UPS, muscle development, and hypertrophy pathways; IIx myonuclei were primarily associated with the UPS, mitochondrial fusion, and adaptive thermogenesis; IIa myonuclei were mainly enriched in adaptive thermogenesis and cellular responses to oxygen levels (Fig. 4 D). Functional enrichment analysis of upregulated genes indicated that IIb, IIx, and IIa myonuclei were all significantly enriched in oxidative stress and apoptosis-related pathways (Fig. 4 D). Volcano plots of DEGs in Fig. 4 C highlighted representative downregulated genes involved in the UPS, such as proteasome subunit Psmd1 , ubiquitin ligase Nedd4l ( 32 ) and ubiquitin substrate transporter Vcp ( 33 ), and mitochondrial pathways, including mitochondrial protein quality control regulator Afg3l2 ( 34 ) and master mitochondrial biogenesis regulator Ppargc1a , as well as upregulated genes involved in cellular stress ( Txnip , Hspb1 )( 35 ) and apoptosis ( Tpt1 , Gsdme )( 36 , 37 ). Notably, Txnip and Tpt1 were among the top 20 upregulated genes in all three myonuclear types of the KO mice (Supplementary Fig. S25D-F). These transcriptional and pathway changes largely matched the proteomics results (decreased UPS, increased stress and apoptosis pathways), also suggesting that Nfe2l1 deletion exerts relatively specific effects on the function of different myonuclear types that are closely related to their metabolic profiles. To further explain the significant changes in metabolites observed in the KO mice, including glycogen accumulation (Supplementary Fig. S25G) and elevated malic acid, triglyceride, and alanine levels (Fig. 3 E-G), we systematically screened for metabolism-related, downregulated genes in the three major myonuclear types (IIb, IIx, and IIa) of KO mice (Supplementary Fig. S25H). Some genes, such as Pnpla3 , Phka1 , and malic enzyme 1 ( Me1 ), showed particularly marked downregulation (Supplementary Fig. S25D-F). By integrating Reactome( 38 ) pathway information, we constructed a schematic diagram of key metabolic reactions to illustrate the relationship between transcriptional changes and metabolic abnormalities (Supplementary Fig. S25I). Specifically, the glycogenolysis-related genes Phka1 , Phkb , and Phkg1 ( 39 ) were significantly downregulated in the KO group, indicating compromised glycogen breakdown capacity in SkM, which was consistent with PAS staining (Supplementary Fig. S25G). In addition, Me1 , a gene encoding an enzyme that catalyzes the conversion of malate to pyruvate( 40 ), also exhibited downregulated expression in the myonuclei of KO mice relative to the Flox group, suggesting that Nfe2l1 deficiency may impair energy metabolism efficiency in muscle fibers. For lipid metabolism, low expression of Pnpla3 may partly explain the accumulation of triglycerides (TG) and diacylglycerol (DG) and the decrease in monoacylglycerol (MG) observed in KO SkM (Fig. 3 F-G). In terms of amino acid metabolism, glutamate-pyruvate transaminase 2 (GPT2), a key enzyme mediating the reversible conversion between alanine and pyruvate( 41 ), exhibited downregulation in KO mice, which suggests a reduction in the connectivity between nitrogen and energy metabolism. In addition, apart from the aforementioned decreased cAMP signaling ( Pde4b , Pde4d ) and adaptive thermogenesis ( Ppargc1a , Esrrg ) pathways (Fig. 4 D and Supplementary Fig. S25H), Nfe2l1 ablation also led to significant downregulation of other important metabolic and signaling regulators, such as energy-sensing genes ( Prkaa2 , Prkag3 )( 42 , 43 ) and glucocorticoid response ( Nr3c1 )( 44 ). Analysis of intergroup differential regulon activity based on the SCENIC further supported the above findings: the activity of STAT5B(+), a regulator of growth factor signaling( 45 ) and NR3C1(+) was significantly decreased in the three types of myonuclei of KO mice, while ESRRG(+) and PPARGC1A(+) activity was significantly reduced in IIx and IIa myonuclei; four regulons related to mitochondrial stress, autoimmunity, and inflammation( 46 , 47 ), including IRF7(+), IRF8(+), JUND(+), and ETS2(+), showed marked increases in all three types of myonuclei in KO mice (Fig. 4 E and Supplementary Fig. S26A-H). To clarify which downregulated genes could be directly attributed to NFE2L1 regulation, we integrated four publicly available NFE2L1 ChIP-seq datasets, identifying 706 high-confidence downstream target genes. Subsequent pathway analysis revealed that the top five pathways were all closely related to the UPS (Supplementary Fig. S27A-D). Overlapping these 706 genes with the 437 significantly downregulated genes across five myonuclear types in KO mice identified 33 downregulated genes that could be directly attributed to Nfe2l1 deletion (Fig. 4 F and Supplementary Fig. S27E-J). These genes were mainly involved in the UPS, including proteasome subunit genes ( PSMA3 , PSMD1 ), E3 ubiquitin ligase ( Rffl )( 48 ), ubiquitinated substrate transport ( Vcp , Nploc4 ), and mitochondrial protein quality control ( Afg3l2 ). Although the network is not exhaustive, these results collectively emphasize the central role of NFE2L1 in the SkM fiber proteostasis regulatory system. Cell-cell communication analysis revealed that both overall communication strength and the number of interactions were decreased in KO mice, but signaling involving IC was significantly increased, particularly between IC and FAP, SC, and APC (Fig. 4 G and Supplementary Fig. S28A-C). Among all signaling pathways, the insulin-like growth factor 1 (IGF1)-insulin-like growth factor 1 receptor (IGF1R) axis was the most prominent (Fig. 4 H and Supplementary Fig. S28D-E), hinglighting its critical role in mediating alterations in the SkM micro-environment in KO mice. Rescue of Nfe2l1 (SM)-KO phenotypes by rolipram treatment. To investigate whether enhancing proteasome function via a posttranslational mechanism could alleviate the phenotypes in KO mice, we employed rolipram, a phosphodiesterase 4 (PDE4) inhibitor, in rescue experiments. Four-week-old male KO mice were treated with rolipram (2 mg/kg BW) or vehicle (saline) for 21 days respectively. Although no significant intergroup differences were observed in body weight, macroscopic appearance, or organ coefficients (Fig. 5 A, C and Supplementary Fig. S29A), running-wheel exercise testing revealed a ~ 2-fold reduction in shock frequency, a surrogate marker of improved exercise tolerance, in rolipram-treated KO mice, approaching statistical significance ( P = 0.052; Fig. 5 B). Histological analysis of quadriceps and gastrocnemius muscles demonstrated marked improvements in rolipram-treated KO mice compared to vehicle controls. The rolipram-treated mice exhibited well-preserved muscle fiber boundaries, intact sarcomeric structures, and reduced basophilic staining, indicative of decreased inflammation or cellular stress (Fig. 5 I, left panels and Supplementary Fig. S29B). Notably, macrophage infiltration was significantly diminished in rolipram-treated KO muscle (Fig. 5 I, right panels). Immunohistochemical staining for the macrophage marker F4/80 further supported the anti-inflammatory effect of rolipram in the KO mice, with treated KO mice exhibiting a substantial reduction in F4/80 + cell infiltration compared to vehicle controls (Fig. 5 I–J and Supplementary Fig. S29C). A bulk RNA-seq analysis identified 169 downregulated and 76 upregulated genes in rolipram-treated vs. vehicle KO mice, with key inflammatory genes ( Nlrp3 , Nfkbiz ) among the most significantly suppressed (Fig. 5 D). GSEA confirmed reduced enrichment of inflammatory response and leukocyte activation pathways, while upregulated processes included C-terminal protein modification and carbohydrate catabolism (Fig. 5 E). Gene set variation analysis (GSVA) revealed enhanced ubiquitin-dependent protein catabolism via the C-end degron pathway and diminished negative regulation of antigen-induced inflammation in rolipram-treated mice (Fig. 5 F–G). RT-qPCR validation showed a consistent downward trend in inflammation-related transcripts ( Adgre1 , Cd68 , Casp1 ) following rolipram treatment (Fig. 5 H). Together, these results demonstrate that rolipram partially rescues skeletal muscle pathology in Nfe2l1 (SM)-KO mice by restoring proteasome-dependent protein homeostasis, highlighting the therapeutic potential of PDE4 inhibition in NFE2L1-associated myopathies. In-depth analysis of Type IIb myonuclei reveals distinct subpopulations and potential myonuclei transitions in Nfe2l1 (SM)-KO mice. To further investigate the alterations of type IIb myonuclei, the most abundant and most significantly affected population in KO mice (Fig. 4 A and D), we performed a systematic analysis of subpopulations within type IIb myonuclei (Fig. 6 ). Composition analysis revealed that type IIb myonuclei could be further divided into seven subpopulations: 0, 1, 2, 3, 5, 6, and 13 (Fig. 4 A and Fig. 6 A). The distribution of these subpopulations differed significantly between the Flox and KO mice: subpopulations 5 and 6 were markedly reduced in KO mice, while subpopulation 1 and the scarcely present subpopulation 13 in Flox mice were dramatically increased in KO mice (Fig. 6 A, right panel and SI Appendix, Table S10). We next identified a total of 2,815 subpopulation-specific characteristic genes, with subpopulation 5 harboring the largest number (722 genes), suggesting its functional diversity and complexity, while subpopulation 0 had the fewest characteristic genes (46 genes) (Supplementary Fig. S30A). K-means clustering was then applied to further group the subpopulations and their characteristic genes (Fig. 6 B), and the top 50 characteristic genes of each subpopulation were visualized as bubble plots (Supplementary Fig. S30B-H). The results showed that subpopulations 5 and 6 shared highly similar transcriptional profiles, whereas subpopulation 13 was markedly distinct from the others. Next, we performed trajectory inference to characterize the potential transition fates of these myonuclei. First, RNA velocity analysis( 49 ) was used to unbiasedly estimate the directionality of nuclear transitions (Supplementary Fig. S31A), followed by Monocle3 pseudotime trajectory analysis( 50 ) (Fig. 6 C). The results revealed that only a single transition path existed in the Flox group (the grey points indicated undetermined states in the Monocle3 pipeline); similar to aerobic exercise, type IIb myonuclei could convert toward IIx and IIa types (blue dashed line). In contrast, two potential trajectories emerged in KO mice: one mirroring Flox mice, with conversion toward IIx myonuclei (blue dashed line); the other involving transitions among subpopulations 5, 1, and 13 (red dashed line). To further elucidate the state, function, and key mechanisms underlying the aberrant transitions (red trajectory) in the KO group, we performed functional enrichment analysis of all characteristic genes for each subpopulation (excluding subpopulation 0 due to the small number of characteristic genes; Supplementary Fig. S31B-G). The main enriched pathways were then subjected to pathway scoring, allowing for systematic comparison among subpopulations and between genotypes (subpopulation 13 in the Flox group was not included in comparisons due to its low abundance—24 nuclei, 0.33%; Fig. 6 D and Supplementary Fig. S32A-P). The results showed that, compared to the other subpopulations, subpopulations 5 and 6 were most prominent in terms of proteasomal protein catabolic process ( Sh3rf2 , Nedd4l ), muscle system process ( Ctnna3 , Pde4d ), muscle hypertrophy ( Sorbs2 , Igfbp5 ), regulation of Wnt signaling pathway ( Cbfb , Gpc5 ), muscle adaptation ( Fbxo32 , Foxo3 ), insulin-like growth factor receptor signaling pathway ( Igfbp5 , Ghr ), rhythmic process ( Rora , Ddx5 ), response to insulin ( Pnpla3 , Stxbp4 ), and cAMP metabolic process ( Pde4d , Pde4b ), with subpopulation 5 being the most significant ( Fig. 6 D and Supplementary Fig. S32-L). Notably, the UPS pathway scores (i.e., proteasomal protein catabolic process) were significantly lower in KO mice across all subpopulations (Supplementary Fig. S32B). We next focused on subpopulations 1 and 13, which were dramatically increased in KO mice. The top 50 characteristic genes of subpopulation 1 displayed characteristics of both subpopulation 5 ( Ctnna3 , Lrrtm3 ) and subpopulation 13 ( Myl1 , Dmd , Flnc , Camk2d ), and were grouped together by K-means clustering (Supplementary Fig. S30F), consistent with the trajectory inference, further supporting that subpopulation 1 represents an intermediate state of transition from subpopulation 5 to subpopulation 13. Pathway scoring showed that key functional signatures, UPS, muscle system process, and response to insulin, were all lower in subpopulation 1 compared to subpopulation 5 (Fig. 6 D and Supplementary Fig. S32A, C and I). Between genotypes, the KO mice exhibited even lower UPS, rhythmic process, and cAMP metabolic process scores in subpopulation 1 (Supplementary Fig. S32B, H and L). These scores further declined in subpopulation 13, which meanwhile possessed the highest scores for stress and apoptosis-related pathways (Fig. 6 D and Supplementary Fig. S32A-P). Cross-species comparison of conserved molecular features between Nfe2l1 (SM)-KO mice and aging-associated type II myonuclear subpopulations in humans. Lai et al.( 51 ) recently constructed multimodal cell atlas of the aging human SkM and identified multiple myonuclear subpopulations closely associated with aging. Among the myonuclei analyzed, aged individuals exhibited either significant increases or an upward trend in “typical” Type I myonuclei (representing the largest cluster among all Type I myonuclei, and defined independently of the positivity for other genes), DCLK1 ⁺(I), ID1 ⁺(I), SAA2 ⁺(I), TNNT2 ⁺(I), DCLK1 ⁺(II), ID1 ⁺(II), SAA2 ⁺(II), and TNNT2 ⁺(II) (Appendix, Fig. S33A-D)( 51 ). Conversely, “typical” Type II myonuclei, the largest cluster among all Type II myonuclei defined independently of other marker genes, and ENOX1 ⁺(II) myonuclei both showed significant age-related decreases (Appendix, Fig. S33A-D). Notably, they pointed out that TNNT2 ⁺, DCLK1 ⁺, ID1 ⁺, and SAA2 ⁺ myonuclei were associated with one or multiple adverse outcomes, including denervation, aging( 52 ), dystrophic repair( 53 ), inflammation, and chronic tissue injury responses( 54 , 55 ). ENOX1 ⁺ myonuclei, on the other hand, likely represent healthy type II fibers, characterized by high expression of genes related to carbohydrate metabolism and circadian rhythm regulation( 51 , 56 ). To investigate the common patterns of metabolic state and fate transition for mouse subpopulations 5 and 13, and assess their evolutionary conservation in humans, we performed a cross-species comparison of different type II myonuclear subpopulations. Figure 7 A shows the UMAP of type II myonuclei from the Lai’s dataset, colored by subpopulation annotation (left), age group (middle), and ENOX1 expression (right). Of the top 50 characteristic genes of mouse subpopulation 5, 40 orthologues were found in Lai’s dataset after conversion to human orthologous genes (Supplementary Fig. S33E-F). K-means clustering revealed that ENOX1 ⁺ (II) and “typical” Type II grouped together. Furthermore, compared to the other four type II myonuclear subpopulations (labeled in red), genes such as MACROD2 , PDE4D , and PHKA1 were expressed at significantly higher levels in ENOX1 ⁺ (II) subpopulation. Notably, the top characteristic gene for mouse subpopulation 5 was Enox2 , a paralog of Enox1 , whereas ENOX2 lacked high expression in any human type II myonuclear subpopulations (Supplementary Fig. S33F). To more intuitively assess the relationship between human type II myonuclear subpopulations and mouse subpopulation 5, we calculated gene set scores based on the 40 orthologues and defined as subpopulation characteristic scores or myonuclear characteristic scores. Both ENOX1 ⁺(II) and “typical” Type II received the highest and second highest scores, respectively, with ENOX1 ⁺(II) scoring significantly higher than SAA2 ⁺ (II) (Fig. 7 B). Similarly, among the top 50 characteristic genes of human ENOX1 ⁺ (II), 33 homologous genes were detectable in the mouse dataset (Supplementary Fig. S33G-H). K-means clustering showed that mouse subpopulations 5 and 6 grouped together, both of which showed markedly higher expression of various ENOX1 ⁺(II) characteristic genes, though Enox1 itself was scarcely expressed across all mouse subpopulations (Supplementary Fig. S33H). Characteristic score analysis further demonstrated that subpopulations 5 and 6 had the highest and second highest scores, while subpopulation 13 scored the lowest (Fig. 7 C). Using a similar approach, we then calculated characteristic scores based on the top 50 characteristic genes from mouse subpopulation 13 and human ID1 ⁺(II) myonuclei with 45 and 42 orthologous genes, respectively (Supplementary Fig. S33I-L). The results showed that human DCLK1 ⁺(II) and ID1 ⁺(II) had the highest and second highest subpopulation 13 characteristic scores, followed by SAA2 ⁺ (II), and all these subpopulations scored significantly higher than ENOX1 ⁺(II) (Fig. 7 D). In mice, subpopulation 13 and subpopulation 2 had the highest and second highest ID1 ⁺(II) characteristic scores, respectively, followed by subpopulation 1, all significantly above subpopulation 5 (Fig. 7 E). We further summarized the overlapping characteristic genes between human ENOX1 ⁺(II) myonuclei and mouse subpopulation 5 (Fig. 7 F and Supplementary Fig. S33M, marked in blue), as well as characteristic genes shared by mouse subpopulation 13 and one or more of the human DCLK1 ⁺(II), ID1 ⁺(II), SAA2 ⁺(II), and TNNT2 ⁺(II) myonuclei (Fig. 7 F and Supplementary Fig. S33M, marked in red). Collectively, cross-species comparison of type II myonuclear characteristics revealed that mouse subpopulation 5, which is dramatically reduced upon Nfe2l1 deletion, shares high functional similarity and substantial molecular overlap with human ENOX1 ⁺ (II) and “typical” Type II myonuclei lost during aging. Conversely, the abnormally expanded subpopulation 13 in KO mice resembled aged-enriched human myonuclear states, with considerable concordance in molecular characteristics. Discussion Our study integrates human genetics, mouse modeling, and multi-omics to establish NFE2L1 as a central regulator of SkM homeostasis. In humans, NFE2L1 ranks among the most SkM-enriched transcription factors, with expression declining in an age-dependent manner, and correlating with sarcopenia severity. UK Biobank analyses revealed robust genetic associations between NFE2L1 variants and appendicular lean mass and hand grip strength, including genome-wide significant loci, underscoring its conserved role in muscle proteostasis. These findings align with co-expression network analyses, which identified enrichment of proteasome subunit genes and ubiquitin-mediated degradation pathways, linking NFE2L1 to the UPS. SkM-specific deletion of Nfe2l1 recapitulated hallmarks of aging, including progressive muscle atrophy, Type IIb fiber loss, and inflammatory response and fat infiltration. Central to these phenotypes is NFE2L1’s regulation of UPS function, including KO mice exhibited downregulation of UPS genes and accumulation of ubiquitinated proteins, accompanied by early-onset ultrastructural defects in 4-week-old muscle, such as sarcomeric disorganization, mitochondrial cristae abnormalities, and sarcoplasmic reticulum dilation. Proteomics and metabolomics revealed early metabolic dysregulation, including glycogen accumulation and lipid peroxidation, and activation of ER and oxidative stress pathways, establishing a hierarchical model where Nfe2l1 loss initiates UPS impairment, triggering compensatory mitochondrial remodeling and metabolic reprogramming that culminate in cellular stress. SnRNA-seq unveiled striking heterogeneity within Type IIb myonuclei. In KO muscle, Type IIb subpopulations 5 and 6 characterized by high expression of UPS and metabolic genes were reduced, while stress/RCD-associated subpopulation 13 expanded. Trajectory inference identified two distinct fates for Type IIb fibers, namely oxidative remodeling toward Type IIx/IIa via ESRRG-mediated mitochondrial biogenesis and degenerative transition to subpopulation 13, marked by Atf3 and RCD genes. Cross-species comparisons with human aging muscle revealed conservation of these characteristics, where mouse subpopulation 5 mirrored “healthy” ENOX1 + type II fibers( 51 ), and subpopulation 13 resembled aging-associated ID1 + / DCLK1 + type II fibers( 51 ), highlighting NFE2L1’s role in preserving functional fiber identity. Nfe2l1 (SM)-KO mice exhibited a pro-inflammatory phenotype, with upregulated macrophage markers ( Adgre1 , Cd68 ) and pyroptosis genes ( Casp1 , Nlrp3 ), and enhanced immune cell-fibroblast communication. Treatment with rolipram, a PDE4 inhibitor, rescued KO phenotypes by enhancing UPS activity via PKA-mediated phosphorylation and suppressing inflammation, reducing F4/80 + infiltration and restoring muscle architecture. These results align with rolipram’s efficacy in tauopathy models( 57 ) and highlight the therapeutic potential of targeting UPS-inflammation crosstalk in NFE2L1-related myopathies. The present study harbors several notable limitations that warrant acknowledgment. First, while NFE2L1 encodes functionally distinct isoforms( 12 , 15 ), this research did not delineate the specific roles of these isoforms within SkM, leaving unresolved questions about their differential contributions to proteostasis. Second, the dynamic transitions of myonuclear states across different age strata in Nfe2l1 (SM)-KO mice remain uncharacterized, constituting a pivotal knowledge gap in deciphering the spatiotemporal regulatory function of NFE2L1 during SkM aging. Third, the systemic effects of rolipram highlight the need for the development of muscle-targeted PDE4 inhibitors to mitigate off-target impacts. Future investigations focusing on isoform-specific functional dissection, multi-timepoint snRNA-seq, and the design of muscle-targeted therapeutic strategies will undoubtedly deepen our comprehension of the molecular mechanisms underlying SkM aging and inform targeted interventional approaches. Collectively, our findings establish NFE2L1 as a critical regulator of SkM proteostasis, linking its decline to age-related degeneration through UPS dysfunction, fiber type attrition, and inflammatory stress. The conserved molecular characteristics between KO mice and aged human muscle position NFE2L1 as a therapeutic target for sarcopenia. By integrating genetic, cellular, and translational insights, this study illuminates new pathways for addressing age-related muscle decline. Materials and Methods Detailed experimental methods, including publicly available RNA-seq and snRNA-seq data mining, CGAS, establishment animal models, analysis of body composition, evaluation of SkM function, protocols for tissue collection, histological examinations, RT-qPCR, Western blot analysis, snRNA-seq data analysis, and statistical analyses, are comprehensively described in the SI Appendix. Animal Care and Use. All animal procedures were conducted in strict accordance with the guidelines of the US National Institutes of Health and approved by the Institutional Animal Care and Use Committee of China Medical University (approval number: CMU20231360, Shenyang, China).​ Mice were housed in specific pathogen-free facilities, with a maximum of four animals per cage. The housing environment was maintained under a 12-hour light/dark cycle. The mice were provided ad libitum access to NIH07 chow diet (Jiangsu Xietong BioTech, Nanjing, China) and reverse osmosis water to ensure proper nutrition and hydration. Histological, Immunohistochemical (IHC), and Immunofluorescence Analyses. Isolated SkM tissues were fixed in 4% paraformaldehyde, followed by paraffin embedding, sectioning, and staining with H&E, IHC or immunofluorescence as described previously( 14 ). Antibodies for F4/80 (c-377009; 1:200; Cell Signaling Technology), ASC/TMS1 (#67824T; 1:1000; CST), MYH7 (BA-D5, 1:50, DSHB), MYH2 (SC-71, 1:50, DSHB), MYH4 (BF-F3, 1:50, DSHB), LAMININ (#11575, 1:50. Abcam) andα-TUBULIN (#7291; 1:1000, Abcam) were used. Bulk RNA-seq. RNA extraction, library preparation, and sequencing were conducted by Seqhealth Technology Co., Ltd. (Wuhan, China) and Personalbio Technology Co., Ltd. (Shanghai, China). Total RNA was extracted from skeletal muscles using TRIzol Reagent (Invitrogen, cat. no. 15596026), including the calf muscles (consisting of the soleus, and gastrocnemius muscles) in 20-week-old mice and the quadriceps muscles of mice in rescue study. snRNA-seq Protocol. Calf muscle samples from three 4-week-old male mice of each genotype were pooled, rinsed with pre-cooled RNase-free saline, minced on ice, and stored at -80°C. Single-nucleus suspension preparation, separation, library construction, and sequencing were performed by Gene Denovo Biotechnology Co. (Guangzhou, China) following established protocols( 14 ). Proteomics Experimental Protocol and Data Analysis. Protein samples were collected from calf muscles of Flox and Nfe2l1 (KM)-KO mice, and analyzed for differentially expressed proteins by mass spectrometry at Beijing Proteome Research Center using the methods described previously( 58 , 59 ). Untargeted Lipidomics and Metabolomics. Approximately 10 mg of -80°C frozen calf muscles (consisting of the soleus and gastrocnemius muscles in mice) samples were subjected to pretreatment and subsequent analyses for untargeted lipidomics and untargeted metabolomics, following previously described protocols. Details was described in supporting information. Rolipram Rescue Study Protocol. Rolipram (HY-16900, MCE) was stored as 50 mg/mL soluble in DMSO. The storage solution is diluted by 100 times using PBS as an application solution. Four-week-old male Nfe2l1 (KM) - KO mice were given rolipram at 2 mg/kg/d by intramuscular injection for 21 consecutive days, followed by metabolic measurements and tissue collection. Control mice were injected with vehicle (PBS). The sample size comprised 7–8 mice per group. Statistics. All statistical analyses were conducted using GraphPad Prism 5 (GraphPad Software, San Diego, CA), with statistical significance defined as P < 0.05. Data are presented as mean ± standard deviation (SD). Student’s t-tests were used for comparisons between two groups, while one-way or two-way analysis of variance (ANOVA) was applied for multi-group comparisons. Declarations Acknowledgments and funding sources Fundings . This research was supported in part by the National Natural Science Foundation of China 82404316 (Z.W), 82020108027 (J.P.), 82173560 (J.F.); Liaoning Provincial Department of Science and Technology 2023JH2/20200159 (Z.W); the Innovation Team Support from China Medical University (CXTD2022004). Declaration of competing interest . The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments . During the writing process of this work, the authors utilized Doubao solely to enhance the language only. 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Sci Adv 7(51):eabl4988 Cong YF et al (2023) Rolipram Ameliorates Memory Deficits and Depression-Like Behavior in APP/PS1/tau Triple Transgenic Mice: Involvement of Neuroinflammation and Apoptosis via cAMP Signaling. Int J Neuropsychopharmacol 26(9):585–598 Shevchenko A et al (2006) In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat Protoc 1(6):2856–2860 Wiśniewski JR, Zougman A, Nagaraj N, Mann M (2009) Universal sample preparation method for proteome analysis. Nat Methods 6(5):359–362 Additional Declarations There is NO Competing Interest. Supplementary Files XSIFiguresV250928.pdf Supporting text, Supplementary Figures S1-33 and Tables S1-11 Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Liu","email":"","orcid":"https://orcid.org/0000-0002-0564-7167","institution":"Dalian Institute of Chemical Physics, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Liu","suffix":""},{"id":527319261,"identity":"b2ae01aa-d949-46ef-a4ac-e368e00d12e6","order_by":11,"name":"Guowang Xu","email":"","orcid":"https://orcid.org/0000-0003-4298-3554","institution":"Dalian Institute of Chemical Physics, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Guowang","middleName":"","lastName":"Xu","suffix":""},{"id":527319262,"identity":"b856cbde-4ef5-4950-a891-e1e2c8366904","order_by":12,"name":"Rui Zhao","email":"","orcid":"","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Zhao","suffix":""},{"id":527319263,"identity":"0429034d-2259-46ab-9436-753c162b4870","order_by":13,"name":"Bei Yang","email":"","orcid":"","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Bei","middleName":"","lastName":"Yang","suffix":""},{"id":527319264,"identity":"82eda8c3-f073-47ce-9d22-f34d4567abae","order_by":14,"name":"Yanyan Chen","email":"","orcid":"","institution":"The First Affiliated Hospital, China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yanyan","middleName":"","lastName":"Chen","suffix":""},{"id":527319265,"identity":"d1045166-dd0c-4e3b-82c1-43bafd8a2d8f","order_by":15,"name":"Yi Wang","email":"","orcid":"","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Wang","suffix":""},{"id":527319266,"identity":"58e50c64-27ad-4745-abae-e3fbbade85d3","order_by":16,"name":"Huihui Wang","email":"","orcid":"https://orcid.org/0000-0001-5545-1982","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huihui","middleName":"","lastName":"Wang","suffix":""},{"id":527319267,"identity":"2882afef-4504-41e3-9a2f-031ade2d153d","order_by":17,"name":"Qiang Zhang","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Zhang","suffix":""},{"id":527319268,"identity":"1c912460-4895-459f-9fc3-67ec8fef3825","order_by":18,"name":"Hongbo Liu","email":"","orcid":"","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongbo","middleName":"","lastName":"Liu","suffix":""},{"id":527319269,"identity":"51f7ce03-3743-4dcd-b8e2-8580f5b84016","order_by":19,"name":"Masayuki Yamamoto","email":"","orcid":"https://orcid.org/0000-0002-9073-9436","institution":"Tohoku University","correspondingAuthor":false,"prefix":"","firstName":"Masayuki","middleName":"","lastName":"Yamamoto","suffix":""},{"id":527319270,"identity":"7b456da5-a286-4712-b031-c4a0614c5278","order_by":20,"name":"Yuanyuan Xu","email":"","orcid":"","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Xu","suffix":""},{"id":527319271,"identity":"23683e37-0ab5-456f-a1aa-ae177b443a7d","order_by":21,"name":"Jingqi Fu","email":"","orcid":"https://orcid.org/0000-0003-3871-428X","institution":"China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jingqi","middleName":"","lastName":"Fu","suffix":""},{"id":527319249,"identity":"89855d12-0f81-4a47-b502-d252a7b65b43","order_by":22,"name":"Jingbo Pi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYBACxhkMDAc+QNgGxGs5OIMkLQwSDAzMPCRpYZ7de/CwTc22xAb25m0SDDV3iHDYnHMJh3OO3U5s4DlWJsFw7BkRWmbkGBzObQBqkcgxk2BsOEykFkuQFvk3pGhhBNvCQ6wWoF8O9hy7bdzGk1ZskXCMCC2Gs3sPf/hRc1u2n/3wxhsfaojR0gCNFDYQkUBYAwODPAMPMcpGwSgYBaNgRAMAIpM9JG8eCkUAAAAASUVORK5CYII=","orcid":"","institution":"China Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jingbo","middleName":"","lastName":"Pi","suffix":""}],"badges":[],"createdAt":"2025-09-28 22:56:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7736640/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7736640/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93995684,"identity":"fb9802e8-427a-41e8-8f26-6a0a56a42879","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":819211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe associations of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNFE2L1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and its target genes with loss of SkM mass and function in human subjects.\u003c/strong\u003e (A-E) Analysis of the transcriptomic data of human SkM tissues from the GTEx dataset (n = 409). The relative mRNA levels (A) and their changes with age (B) of the top 10 transcription factors ranked by mean mRNA expression. (C) The mRNA levels of \u003cem\u003eNFE2L1\u003c/em\u003e among different gender and age groups. \u003cem\u003eP\u003c/em\u003e-trend was obtained from the Jonckheere trend test, see SI Appendix, Figure S2 and Table S1 for the details. (D and E) Enrichment analysis of \u003cem\u003eNFE2L1\u003c/em\u003e co-expressed genes using the human C3 collection via MSigDB (D) and KEGG database (E). (F) mRNA levels of \u003cem\u003eNFE2L1\u003c/em\u003e in the SkM tissues (vastus lateralis) from young healthy subjects (n = 19), older healthy subjects (n = 29), and sarcopenia patients (n = 24) in the GSE167186 dataset. \u003cem\u003eP\u003c/em\u003e-trend was obtained from the Jonckheere trend test. Differential expression analysis (DEA) among groups was performed using DESeq2, and the results are presented in SI Appendix, Table S3 and S4. (G and H) In-depth analysis of the public dataset GSE200398 which encompasses RNA-seq data of SkM (vastus lateralis of the left leg) from subjects in the slow-twitch group (n = 12), characterized by a lower percentage of fast-twitch muscle fibers, and the fast-twitch group (n = 11), featuring a higher percentage of fast-twitch muscle fibers. For detailed information, refer to SI Appendix, Figure S4. Heat map (G) depicting significant differential expression patterns of marker genes for slow- and fast-twitch muscle fibers, \u003cem\u003eNFE2L1\u003c/em\u003e, and proteasome subunit genes between the groups. Colors represent standardized gene expression levels (z-score). Correlation analysis (H) between \u003cem\u003eNFE2L1\u003c/em\u003eexpression levels and the percentage of fast-twitch muscle fibers among the subjects in the slow-twitch group (green) and fast-twitch group (orange). \u003cem\u003eR\u003c/em\u003e, Pearson correlation coefficient; \u003cem\u003eP\u003c/em\u003e, two-sided \u003cem\u003eP\u003c/em\u003e-value; centre represents the average value; shade indicates 95% confidence interval. (I) The associations of \u003cem\u003eNFE2L1\u003c/em\u003e variants with lean mass in a candidate gene association study using the UKB cohort. Details see SI Appendix, Table S5 and S6.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/5ce92300acb597d29b2b8c40.jpg"},{"id":93995682,"identity":"9e17aff6-b418-4d89-844f-9c24db6fbaf8","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":917601,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe impacts of striated muscle-specific deletion of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNfe2l1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e on SkM in male mice\u003c/strong\u003e. (A) The body weight change with age. n = 6-11. Cre, \u003cem\u003eCkm\u003c/em\u003e-Cre; Flox, \u003cem\u003eNfe2l1\u003c/em\u003e-Floxed; KO, \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO; \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Flox at the same age. \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Cre at the same age. (B) Representative images of gross morphology of SkM. n = 5. Animal age = 20 ± 2 weeks. Quad, quadriceps; Gas, gastrocnemius; Tri, triceps brachii. (C) The relative tissue weights. n = 3-7. Animal age = 20 ± 2 weeks. The statistical significances were determined using a one-way ANOVA. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Flox at the same age. \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Cre at the same age. (D) Representative images of H\u0026amp;E staining of quadriceps muscles in mice. n = 6. Animal age = 4 ± 1 weeks (4 W), 20 ± 2 weeks (20 W) or 50 ± 5 weeks (50 W). Scale bar, 100 µm. (E) The GSEA results of proteasome pathway (upper panel) and chemokine signaling pathway (lower panel) using the transcriptomic data of calf muscles from 20 weeks old mice. n = 3. (F) The mRNA levels measured by RT-qPCR in quadriceps muscles. n = 4. Animal age = 20 ± 2 weeks. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Flox. (G) Representative images of IHC of F4/80 (upper panels), ASC/TMS1 (middle panels) and Oil-red O staining (lower panels) of quadriceps muscles from 20 weeks old mice. Scale bar: 100 µm. n = 4. (H and I) Representative images (H) and quantification (I) of immunofluorescence staining of calf muscles. n = 3-5. Animal age = 20 ± 2 weeks. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 vs Flox. (J) Heat map of mRNA expression of markers for type I (\u003cem\u003eMyh7\u003c/em\u003e), type IIa (\u003cem\u003eMyh2\u003c/em\u003e), and type IIb (\u003cem\u003eMyh4\u003c/em\u003e) fibers. n = 3. Animal age = 20 ± 2 weeks. The mRNA levels were measured by RNA-seq.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/2d80af7ceee613fbc4ceb92c.jpg"},{"id":93996787,"identity":"4be8605e-dede-414a-93c4-225630d5d4dd","added_by":"auto","created_at":"2025-10-21 07:12:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":909773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic profiling and metabolomic analysis of calf muscles from 4-week-old Flox and KO male mice.\u003c/strong\u003e (A) The relative tissue weights. n = 3-12. Animal age = 4 ± 1 weeks. The statistical significances were determined using a one-way ANOVA. (B) Electron micrograph of quadriceps muscles from 4 weeks old mice. \u003csup\u003e*\u003c/sup\u003e shows a mitochondrion. \u003csup\u003e# \u003c/sup\u003eshows sarcoplasmic reticulum lumen.\u0026nbsp; Scale bar, 3 µm. (C) Bubble plot of proteomic GSEA results, where the shape, size, and color represent the database used, statistical significance, and direction of regulation, respectively. n = 4. GSEA: Gene set enrichment analysis. (D) Heatmap showing the expression levels (z score) of selected significantly downregulated (left panel) and upregulated (right panel) proteins. 1-4 indicate individual mice. Downregulated proteins are all related to the UPS, while upregulated proteins are associated with ERS or apoptosis processes. Pathway annotation is based on the BP terms of the GO database. (E) Metabolite set enrichment analysis (MSEA) results of untargeted metabolomics, presenting the most significant or biologically interesting differential metabolic pathways. (F) Heatmap showing significantly upregulated and downregulated metabolite levels (z score) in the untargeted metabolomic analysis. 1-12 indicate individual mice. (G) Heatmap of significantly upregulated and downregulated lipid metabolite levels (z score) in targeted lipidomics. 2-12 indicate individual mice.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/03a44443c2e2b31299807dbb.jpg"},{"id":93995681,"identity":"a5a6605a-b049-4a5f-946d-c58500364751","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":822425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle-nucleus transcriptomic profiling of calf muscles of 4-week-old Flox and KO male mice. \u003c/strong\u003e(A) UMAP visualization of 12 nuclear types (32,112 nuclei, left panel) and the proportion of each cell nucleus type (right panel). Calf muscle samples were collected from 6 mice of each genotype (4 weeks old, male) and then pooled for nuclear isolation. (B) Bubble plot showing marker genes for each nuclear type. Bubble size represents the percentage of cells expressing the marker genes, and bubble color represents the mean expression level (z score). (C) Volcano plots of differentially expressed genes between KO and Flox groups in type IIb (left panel), type IIx (middle panel), and type IIa (right panel) myonuclei. Genes of interest that are downregulated and upregulated are highlighted in blue and red, respectively. (D) Bubble plot showing representative pathways from enrichment analysis of upregulated genes (red) and downregulated genes (blue) in IIb, IIx, and IIa myonuclei in the KO group relative to the Flox group. Bubble color and size represent the direction of regulation and significance, respectively. IIb, type IIb myonuclei; IIx, type IIx myonuclei; IIa, type IIa myonuclei. (E) Ranked dot plot (sorted by significance level) showing regulons that are upregulated (red) and downregulated (blue) in IIb, IIx, and IIa myonuclei in the KO group relative to the Flox group. Regulons such as STAT5B (+) refer to transcription factors and their regulatory gene networks identified through SCENIC analysis. For details, see SI Appendix, Figure S26. (F) Partial regulatory network of NFE2L1. This network was constructed by integrating publicly available ChIP-seq data targeting NFE2L1 (see SI Appendix, Figure S27) with all downregulated genes (converted to human orthologs) found in five types of myonuclei in the KO group relative to the Flox group. (G) Heat map showing differential signal communication intensity among cell types. Y-axis, signal-emitting cell type; X-axis, signal-receiving cell type. The CellChat analysis pipeline with default parameters was used to infer differential cell communication, specific ligands, and receptors for Flox and KO groups. Blue represents decrease, red represents increase. Due to infinite values generated by calculating relative values, the color bar does not display red, and the number of differential signal communications is shown in SI Appendix, Figure S28. (H) Chord diagrams showing details of the IGF signaling pathway network in Flox (left panel) and KO (right panel) groups, respectively.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/fb5bfff7ecc737e8eb8c8c7c.jpg"},{"id":93996016,"identity":"7b29de99-754b-4993-8922-e176efceb5b2","added_by":"auto","created_at":"2025-10-21 07:04:40","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":954737,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe impact of rolipram treatment on the SkM phenotype of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNfe2l1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e(SM)-KO mice\u003c/strong\u003e. Male \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice at four weeks of age received rolipram (at a dose of 2 mg/kg) through intramuscular injection for a period of 21 days. n = 7-8. Veh, \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice with vehicle (saline); Roli, \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice with rolipram treatment. (A) The body weight of the mice after they underwent the rolipram treatment. (B) The frequency of electric shocks at the time when the control mice run to fatigue point. (C) The relative weights of various tissues in the mice that had been administered rolipram. Quad, quadriceps; Gas, gastrocnemius; Sol, soleus; Tri, triceps brachii; TA, tibialis anterior. (D) Heat map illustrating 169 genes showing downregulation and 76 genes exhibiting upregulation in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice that were treated with rolipram relative to the untreated \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO control mice. FPKM values of gene expression were z-score transformed and the range was restricted to -2 to 2 for better visualization. (E) GSEA results showing the most significantly upregulated and downregulated biological pathways that were caused by the treatment with rolipram in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice. The biological processes (BP) of the GO database were used. (F and G) The impacts of rolipram treatment on the ubiquitin-dependent protein catabolic process via the C-end degron rule pathway (F) and inflammatory response to antigenic stimulus (G) based on GSVA. Two-sided Wilcoxon rank-sum tests were used for the comparisons between groups. (H) The mRNA levels measured by RT-qPCR in quadriceps muscles. (I and J) Representative H\u0026amp;E stainings in quadriceps and gastrocnemius muscles of mice (left panels). Representative images (I, right panels) and quantifications (J) of IHC of F4/80 in quadriceps and gastrocnemius muscles. Scale bar: 200 µm.\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/f51c6b262926c656105f968b.jpg"},{"id":93995688,"identity":"29151f1c-c7ed-434c-ad81-71418aef28c5","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1017602,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eNfe2l1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e deficiency leads to alterations in subpopulations of type IIb myonuclei.\u003c/strong\u003e (A) UMAP visualization of subpopulations of type IIb myonuclei (left panel) and the percentage of each subpopulation (right panel, sorted in descending order by percentage in the Flox group). The subpopulation numbers (0, 1, 2, 3, 5, 6, 13) were derived from the initial Seurat clustering analysis (see SI Appendix, Figure S23). Subpopulation proportions were calculated as the number of cells per subpopulation over the total number of type IIb myonuclei (see SI Appendix, Table S10). (B) Clustered heatmap of characteristic genes for each type IIb myonuclear subpopulation. Rows represent genes and columns represent type IIb myonuclear subpopulations, both clustered by k-means. The color indicates normalized mean gene expression (z score). (C) Pseudo-time trajectory analysis of type IIb myonuclei in Flox (left) and KO (right) groups using the Monocle3 analysis pipeline. Colors represent the progression of pseudo-time, with gray indicating states beyond reachable pseudo-time. Dashed arrows were manually added to illustrate potential myonuclear fate transition pathways based on pseudo-time analysis results. (D) Pathway activity score analysis for each subpopulation of type IIb myonuclei. Column annotations include group and subpopulation number. Each row label indicates the pathway name (in red), with representative genes for each pathway listed below in parentheses (in black). The color of each bubble represents the mean pathway activity score (z score), and the bubble size indicates the percentage of cells in the subpopulation with positive pathway activity scores. The selection criteria for pathways and representative genes are described in SI Appendix, Figure S31B-G, and comparative analyses of pathway scores among subpopulations and between groups within the same subpopulation are provided in SI Appendix, Figure S32A-P.\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/1a6db3fa695669b5b4ab6463.jpg"},{"id":93995686,"identity":"38e60bb7-f9c4-42a6-9f74-b6884e81a82a","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":751881,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative analysis of human skeletal muscle aging and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNfe2l1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e deficiency in mice\u003c/strong\u003e. (A) UMAP plots showing the distribution of type II myonuclei from aged human skeletal muscle in the publicly available Lai’sdataset(51), colored by myonuclear annotation (left), age group (middle), and normalized \u003cem\u003eENOX1\u003c/em\u003eexpression level (right). UMAP embedding, myonuclear annotation, and grouping information are derived from the original dataset. The distribution and proportions of all myonuclei are presented in SI Appendix, Figure S33A-D. (B) Violin plots illustrating the distribution of characteristic gene scores for cluster 5 (this study) across different type II myonuclear subpopulations in the Lai’s dataset. The x-axis represents various type II myonuclear subpopulations, ordered by median characteristic gene score in descending order. Myonuclear subpopulations labeled in blue text (\u003cem\u003eENOX1\u003c/em\u003e⁺ (II), Type II, and Cluster 5) represent those with decreased proportions in the aged group (Lai’sdataset) or in KO mice (this study); myonuclear subpopulations labeled in red text (such as \u003cem\u003eSAA2\u003c/em\u003e⁺ (II), etc.) represent those with increased proportions in the aged group (Lai’sdataset) or in KO mice (this study). (C) Violin plots showing the distribution of \u003cem\u003eENOX1\u003c/em\u003e⁺ (II) characteristic gene scores across IIb myonuclear subpopulations in the mouse dataset from this study. The ordering and color labeling are consistent with panel (B). (D) Same as panel (B), but illustrating the distribution of cluster 13 characteristic gene scores. (E) Same as panel (C), but showing the distribution of \u003cem\u003eID1\u003c/em\u003e⁺ (II) characteristic gene scores. (F) Bubble plot showing the expression levels of genes across different type II myonuclear subpopulations in the Lai’s dataset. The genes include \u003cem\u003eENOX1\u003c/em\u003e, \u003cem\u003eENOX2\u003c/em\u003e and shared characteristic genes between human \u003cem\u003eENOX1\u003c/em\u003e⁺ (II) or Type II and mouse subpopulation 5 (blue text); and characteristic genes shared between mouse subpopulation 13 and any one or more of the human \u003cem\u003eDCLK1\u003c/em\u003e⁺ (II), \u003cem\u003eID1\u003c/em\u003e⁺ (II), \u003cem\u003eSAA2\u003c/em\u003e⁺ (II), and \u003cem\u003eTNNT2\u003c/em\u003e⁺ (II) myonuclear types (red text). The mouse homologs of these genes and their expression profiles in each IIb subpopulation in the mouse dataset are shown in SI Appendix, Figure S33M. Columns are organized using k-means clustering. Bubble color represents the mean expression level (z score), and bubble size indicates the percentage of expressing cells. For panels B–E, the gene sets used for characteristic gene score calculation are listed in SI Appendix, Figure S33E–L. \u003cem\u003eP\u003c/em\u003e values are calculated using the two-sided Wilcoxon rank-sum tests.\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/d8018a5387f99c3c21bde605.jpg"},{"id":93995687,"identity":"759ad0ad-9b5d-460a-b221-7ad2a78bfb64","added_by":"auto","created_at":"2025-10-21 06:56:40","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":382542,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic diagram of the core findings in this study.\u003c/strong\u003e Skeletal muscle undergoes atrophy during human aging, involving many mechanisms, of which NFE2L1-UPS dysfunction may be one. According to consensus, fast-twitch and slow-twitch muscle fibers can be interconverted in normal mice (e.g., Flox mice) through changes in exercise patterns and dietary habits (green bidirectional dashed lines, bottom left). In contrast, muscle fibers in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice lose NFE2L1-UPS function, leading to elevated stress levels, which in turn cause type IIb muscle fibers to undergo core functional decline and ultimately regulated cell death (red unidirectional dashed lines, bottom right) on one hand; on the other hand, they may also lose muscle fiber identity through mechanisms such as stress-driven metabolic reprogramming (blue unidirectional dashed lines, bottom right).\u003c/p\u003e","description":"","filename":"Fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/d393f9a24bc02fcf08885b8e.jpg"},{"id":94211269,"identity":"b7c4fc67-08ab-4374-b2ef-6b0b9c5cbce6","added_by":"auto","created_at":"2025-10-23 15:43:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7980238,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/baa64500-0425-465e-bd8c-497d9ca06f89.pdf"},{"id":93995689,"identity":"d08f229b-972a-458e-abd8-1dfda3b019a5","added_by":"auto","created_at":"2025-10-21 06:56:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21664604,"visible":true,"origin":"","legend":"Supporting text, Supplementary Figures S1-33 and Tables S1-11","description":"","filename":"XSIFiguresV250928.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7736640/v1/c6258ed82cc2579215117a9b.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"NRF1/NFE2L1 orchestrates spatiotemporal regulation of protein degradation network in skeletal muscle","fulltext":[{"header":"Significance Statement","content":"\u003cp\u003eSkeletal muscle decline during aging is linked to impaired proteostasis and cell death. This study identifies NFE2L1 as a key regulator of the ubiquitin-proteasome system, controlling muscle fiber-type integrity and suppressing regulated cell death. Genetic and pharmacological evidence in mice and humans reveals NFE2L1 maintains proteostasis and metabolic balance, offering a therapeutic target to combat age-related muscle atrophy and functional decline.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSkeletal muscle (SkM), a central hub for movement, postural support, and metabolic balance, is unparalleled in its dynamic regulation of protein synthesis and catabolism, processes fundamental to its structural integrity and functional adaptability(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Dysregulation of SkM protein metabolism, which is instigated by aging, denervation, physical inactivity, nutritional stress, or disease, underlies a spectrum of pathological states, most notably SkM atrophy(\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Maintaining equilibrium in SkM protein turnover is therefore essential for preserving muscle health and functional capacity across the lifespan.\u003c/p\u003e\u003cp\u003eHuman SkM comprises slow-twitch (Type I) and fast-twitch (Type II) fibers, with Type II further subclassified into IIa and IIx subtypes, each exhibiting distinct profiles of protein synthesis and degradation(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In mice, SkM also includes Type IIb fibers. The contraction velocity increases in the order of Type I, Type IIa, Type IIx, and Type IIb. Type I fibers, endowed with abundant mitochondria and capillaries, rely on oxidative metabolism to sustain stable protein synthesis, supported by a balanced interplay between autophagy-lysosome and ubiquitin-proteasome systems (UPS) that ensures protein quality control and fiber integrity, making them well-suited for prolonged, low-intensity aerobic activities. With aging, Type I fibers demonstrate relative resilience in maintaining oxidative capacity and fiber morphology(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In contrast, Type II fibers which is critical for explosive, high-intensity movements exhibit rapid activation of the mechanistic target of rapamycin complex 1 (mTORC1) pathway to enhance protein synthesis in response to exercise, coupled with a highly active UPS that accelerates protein degradation during transient metabolic stress, such as fatigue or energy flux, to fuel contraction(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This plasticity renders Type II fibers more susceptible to post-exercise protein loss. Aging exacerbates Type II fiber vulnerability, driving selective atrophy of IIx/IIb subtypes, blunting anabolic responsiveness, and skewing fiber composition toward a higher Type I proportion, a shift linked to neuromuscular, hormonal, and inflammatory perturbations in fiber-specific protein turnover.\u003c/p\u003e\u003cp\u003eDysfunction of the UPS in SkM fibers leads to accumulation of damaged proteins, forming aggregates that induce stress responses and disrupt cellular homeostasis(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Severe stress triggers regulated cell death (RCD), such as apoptosis, necroptosis, pyroptosis and panoptosis, culminating in fiber loss, reduced muscle mass, and strength decline(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). UPS impairment also compromises muscle stem cell function, hindering regenerative capacity(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Given the inherently higher UPS activity in Type II fibers, these subtypes are particularly sensitive to UPS deficiency or dysfunction.\u003c/p\u003e\u003cp\u003eNuclear factor (erythroid-derived 2)-like 1 (NFE2L1/NRF1), a conserved CNC-bZIP transcription factor, acts as a master regulator of proteasome homeostasis, integrating redox balance with proteasome subunit gene expression(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Under basal conditions, NFE2L1 maintains low protein abundance via post-translational regulation while driving constitutive transcription of proteasome subunits to sustain basal proteasome activity. Upon cellular stress, including oxidative, endoplasmic reticulum (ER), and proteotoxic stress, activated NFE2L1 translocates to the nucleus, where it binds antioxidant response elements (AREs) in proteasome subunit promoters to upregulate gene expression and enhance damaged protein clearance(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Its regulatory output is further refined by alternative splicing and dynamic post-translational modifications, including glycosylation, phosphorylation, and ubiquitination, which modulate its stability, nuclear localization, and DNA-binding affinity to fine-tune proteasome biogenesis and cellular stress resilience(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough previous investigations have firmly established the UPS as a fundamental pillar of SkM homeostasis and implicated NFE2L1 in proteasome regulation, the fiber-type-specific functions of NFE2L1 within SkM remain largely unexplored. In this study, we comprehensively integrated publicly available chromatin immunoprecipitation sequencing (ChIP-Seq) and transcriptome datasets from aging and sarcopenia cohorts, aiming to elucidate the spatiotemporal patterns of NFE2L1 expression and transcriptional activity in SkM. By leveraging the extensive UK Biobank cohort, we successfully identified genetic variants in NFE2L1 that were significantly associated with lean muscle mass and grip strength. Using striated muscle-specific \u003cem\u003eNfe2l1\u003c/em\u003e-knockout mice (\u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO), we provided robust evidence of \u003cem\u003eNfe2l1\u003c/em\u003e deficiency-induced and age-dependent progressive SkM atrophy. This atrophy was characterized by the preferential loss of Type IIb fibers, activation of regulated cell death (RCD) pathways, chronic inflammation, and fibrotic changes. Through proteomics, untargeted metabolomics, and lipidomics, we further delineated a NFE2L1-driven regulatory network in SkM, thereby highlighting its pivotal role in maintaining UPS function and regulating downstream metabolic pathways. Single-nucleus RNA sequencing (snRNA-Seq) revealed a global decline in UPS function and elevated cellular stress across various myonuclei subtypes in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO muscle. Notably, this was accompanied by the depletion of a myonuclear state characterized by high UPS activity and a pronounced shift toward RCD-susceptible states. Moreover, pharmacological intervention with rolipram, a selective activator of the cAMP-PKA pathway that enhances proteasome function, partially reversed these pathological phenotypes in juvenile \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice. Analyses of human aging SkM datasets further validated our findings, underscoring the conserved nature of myonuclear state transitions during SkM senescence. Collectively, our results firmly establish NFE2L1 as a critical spatiotemporal regulator of proteostasis in SkM, offering novel insights into the mechanisms underlying aging-related muscle decline and paving the way for potential therapeutic interventions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eThe associations of\u003c/b\u003e \u003cb\u003eNFE2L1\u003c/b\u003e \u003cb\u003ewith SkM mass and function in humans.\u003c/b\u003e To elucidate the pivotal role of NFE2L1 in SkM, we conducted an in-depth analysis of the mRNA abundance of 1,839 human transcription factors (TFs) using the Genotype-Tissue Expression (GTEx) dataset(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), which encompassed 263 male and 146 female subjects. Notably, \u003cem\u003eNFE2L1\u003c/em\u003e emerged as one of the top-ranking TFs in SkM, securing the fourth position among the most enriched TFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Further exploration revealed that, when compared to other tissues, SkM exhibited the highest \u003cem\u003eNFE2L1\u003c/em\u003e mRNA levels (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), emphasizing its tissue-specific prominence. In addition, among the 10 most highly expressed TFs in SkM, \u003cem\u003eNFE2L1\u003c/em\u003e stood out uniquely, as it was the only factor demonstrating an age-dependent decline trend (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In addition, the trend analyses conducted separately for male and female cohorts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Supplementary Fig. S2A and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) provided robust validation of this age-related decrease, indicating a potential role of NFE2L1 in age-associated SkM changes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo comprehensively define the regulatory network of NFE2L1 in SkM, we computed the Pearson correlation coefficient between \u003cem\u003eNFE2L1\u003c/em\u003e and all other genes within SkM samples. Genes were meticulously selected based on stringent criteria: those with a correlation coefficient \u003cem\u003eR\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. This process yielded a total of 1,465 genes that were co-expressed with \u003cem\u003eNFE2L1\u003c/em\u003e. Among these, notable gene categories included proteasome subunit genes, such as \u003cem\u003ePSMD7\u003c/em\u003e, \u003cem\u003ePSMD2\u003c/em\u003e, \u003cem\u003ePSMD11\u003c/em\u003e, \u003cem\u003ePSMB5\u003c/em\u003e, \u003cem\u003ePSMD3\u003c/em\u003e, and \u003cem\u003ePSMD1\u003c/em\u003e, as well as antioxidant-related genes, such as \u003cem\u003eSQSTM1\u003c/em\u003e, \u003cem\u003eME1\u003c/em\u003e, \u003cem\u003eGSR\u003c/em\u003e, \u003cem\u003eSOD1\u003c/em\u003e, \u003cem\u003eGCLC\u003c/em\u003e, and \u003cem\u003eSOD2\u003c/em\u003e (Supplementary Fig. S2B-C). In addition, we performed an enrichment analysis on the co-expressed genes using the human C3 gene sets from the Molecular Signatures Database (MSigDB)(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This analysis led to the identification of the term \"NFE2L1_TARGET_GENE,\" which includes 253 potential target genes of NFE2L1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD and SI Appendix, Table S2). Leveraging the STRING(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) website for protein-protein interaction analysis and visualizing the results with Cytoscape, we determined that the UPS was the most prominent network (Supplementary Fig. S2D). Additionally, KEGG enrichment analysis of the 1,465 co-expressed genes highlighted the proteasome pathway and ubiquitin-mediated protein degradation as the most significant biological processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eFurthermore, we analyzed the GSE167186 dataset, which comprised 19 young healthy subjects, 29 older healthy subjects, and 24 sarcopenia patients (Supplementary Fig. S2E). Our analysis revealed a significant decreasing trend in \u003cem\u003eNFE2L1\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Through differential expression analysis (DEA), we further identified a notable reduction in the expression levels of numerous proteasome subunit genes (Supplementary Fig. S2F and Table S3 and S4). To validate our findings, we explored another public dataset, GSE175495. Consistent with our previous results, we observed that the expression of \u003cem\u003eNFE2L1\u003c/em\u003e was significantly lower in the older group (n\u0026thinsp;=\u0026thinsp;11) compared to the younger group (n\u0026thinsp;=\u0026thinsp;12) (Supplementary Fig. S3A). Subsequently, we conducted an enrichment analysis on the 314 genes co-expressed with \u003cem\u003eNFE2L1\u003c/em\u003e. The analysis highlighted that the most significant terms were \"NFE2L1_TARGET_GENE\" (Supplementary Fig. S3B) and biological processes related to the UPS (Supplementary Fig. S3C). Moreover, a substantial number of proteasome subunit genes exhibited significantly decreased mRNA expression in the aged group (Supplementary Fig. S3D). To investigate the expression patterns of \u003cem\u003eNFE2L1\u003c/em\u003e in fast-twitch and slow-twitch muscle fibers, we further analyzed the public dataset GSE200398. This dataset includes 11 samples with a high percentage of fast-twitch fibers (defined as the Fast group) and 12 samples with a low percentage of fast-twitch fibers (defined as the Slow group) (Supplementary Fig. S4A-D). The results showed that the expression levels of \u003cem\u003eNFE2L1\u003c/em\u003e and proteasome subunit genes were significantly higher in the Fast group than those in the Slow group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). In addition, correlation analysis within groups revealed that, in the Fast group, \u003cem\u003eNFE2L1\u003c/em\u003e expression was significantly positively correlated with the percentage of fast-twitch fibers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH), whereas no significant correlation was observed in the Slow group. These findings collectively highlight the important role of NFE2L1 in regulating UPS homeostasis in SkM, as well as its potential involvement in age-related skeletal muscle alterations.\u003c/p\u003e\u003cp\u003eTo dig deeper into the relationship between \u003cem\u003eNFE2L1\u003c/em\u003e and SkM mass and function, we carried out a candidate gene association study (CGAS) utilizing the extensive UK Biobank (UKB)(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) cohort. Our analysis encompassed a vast sample size: 367,942 participants (197,749 females and 170,193 males) for hand grip strength (HGS) assessment and 353,086 participants (189,591 females and 163,495 males) for appendicular lean mass (ALM) evaluation. Applying a highly stringent significance threshold of 1.04\u0026times;10⁻⁴, we detected significant associations for all the studied traits. Specifically, 14 variants were found to be linked with ALM, while 6 variants were associated with HGS. Following the exclusion of non-replicated variants across genders, 13 variants remained associated with ALM and 6 with HGS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI and Supplementary Fig. S5 and Table S5-6). Notably, several of these associations achieved genome-wide significance (α\u0026thinsp;=\u0026thinsp;5.0\u0026times;10⁻⁸), providing compelling evidence that NFE2L1 may play a crucial and fundamental role in human SkM biology, potentially influencing both muscle mass and functional capacity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeneration and phenotypic characterization of striated muscle-specific\u003c/b\u003e \u003cb\u003eNfe2l1\u003c/b\u003e \u003cb\u003eknockout mice.\u003c/b\u003e To characterize the function of NFE2L1 in SkM, we generated \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO (KO) mice by crossing \u003cem\u003eNfe2l1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e (Flox) mice with \u003cem\u003eCkm\u003c/em\u003e-Cre\u003csup\u003e+/-\u003c/sup\u003emice (Cre). Quantitative analysis revealed a 61.6% reduction in \u003cem\u003eNfe2l1\u003c/em\u003e mRNA expression in SkM of KO mice compared to littermate Flox controls, with no significant changes in liver expression, confirming muscle-specific gene ablation (Supplementary Fig. S6A). Immunoblotting using a pan-NFE2L1 antibody detected diminished protein isoforms (25\u0026ndash;140 kDa) in KO SkM relative to Flox littermates (Supplementary Fig. S6B), validating successful generation of the KO model for functional studies.\u003c/p\u003e\u003cp\u003eMale KO mice exhibited significant reductions in body weight gain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), lean mass (Supplementary Fig. S7A), and SkM mass (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u0026ndash;C and Supplementary Fig. S9), accompanied by increased fat mass (Supplementary Fig. S7B), compared to control littermates. Functional assessments in 20-week-old male KO mice revealed profound declines in athletic performance. The grip strength of KO mice was reduced by 17.3% (Supplementary Fig. S8A), hanging time during rotarod testing decreased by 61.8% (Supplementary Fig. S8C), and the number of stopped moving (measured by shock events) during the running wheel test was doubled compared to Flox controls (Supplementary Fig. S8B), indicating compromised motor coordination and endurance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHistopathological analysis by H\u0026amp;E staining showed no significant genotype-specific differences in quadriceps muscles at 4 weeks of age (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and SI Appendix Fig. S10). By 20 weeks, KO mice exhibited striking alterations, including myocyte size heterogeneity, ectopic nuclear localization in the cytoplasm, cytoplasmic structural disintegration with indistinct boundaries, and increased aggregates of inflammatory cells and adipocyte infiltration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and SI Appendix Fig. S11 A-D). At 50 weeks, muscle pathology worsened, characterized by severe muscle fiber atrophy and loss, along with heightened inflammatory cell and adipocyte infiltration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and SI Appendix Fig. S12). These changes were not limited to quadriceps but also observed in gastrocnemius and triceps brachii muscles (SI Appendix Fig. S13), and identical phenotypic alterations were recapitulated in female KO mice (SI Appendix Fig. S14 A-I).\u003c/p\u003e\u003cp\u003eTo investigate the molecular basis of these phenotypes, RNA-seq was performed on SkM tissues from 20-week-old KO and Flox mice, identifying 586 significantly downregulated genes (e.g., proteasome subunit genes \u003cem\u003ePsmd1\u003c/em\u003e, \u003cem\u003ePsmd3\u003c/em\u003e, \u003cem\u003ePsmc2\u003c/em\u003e) and 1,066 upregulated genes (e.g., inflammatory response gene \u003cem\u003eCx3cl1\u003c/em\u003e and apoptosis-related genes \u003cem\u003eTlr4\u003c/em\u003e, \u003cem\u003eCasp3\u003c/em\u003e) (Supplementary Fig. S16A-C). Gene set enrichment analysis (GSEA) confirmed significant downregulation of the proteasome pathway and upregulation of chemokine signaling associated with inflammation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). RT-qPCR validation revealed marked upregulation of macrophage markers (\u003cem\u003eAdgre1\u003c/em\u003e, \u003cem\u003eCd68\u003c/em\u003e), pyroptosis-related genes (\u003cem\u003eCasp1\u003c/em\u003e, \u003cem\u003eNlrp3\u003c/em\u003e, \u003cem\u003ePycard\u003c/em\u003e) in KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Immunohistochemical staining for apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), which is also known as target of methylation-induced silencing (TMS1), and F4/80 (macrophages), along with Oil-Red O staining, demonstrated increased inflammation, RCD and intramuscular fat infiltration in KO muscle tissues compared to Flox controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG and SI Appendix Fig. S15 A-C, S17 A-B).\u003c/p\u003e\u003cp\u003eTo explore fiber type-specific effects of \u003cem\u003eNfe2l1\u003c/em\u003e deficiency, we analyzed expression of muscle fiber marker genes including \u003cem\u003eMyh4\u003c/em\u003e (Type IIb), \u003cem\u003eMyh2\u003c/em\u003e (Type IIa), and \u003cem\u003eMyh7\u003c/em\u003e (Type I). RNA-seq data analysis showed decreased \u003cem\u003eMyh4\u003c/em\u003e expression and increased \u003cem\u003eMyh2\u003c/em\u003e/\u003cem\u003eMyh7\u003c/em\u003e levels in KO SkM (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ). Immunofluorescence staining in calf triceps muscle confirmed a 57.6% reduction in Type IIb fibers (MYH4\u003csup\u003e+\u003c/sup\u003e), while the proportion of Type I fibers (MYH7\u003csup\u003e+\u003c/sup\u003e) was significantly increased, and a trend toward increased Type IIa fibers (MYH2\u003csup\u003e+\u003c/sup\u003e) in KO mice compared to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH\u0026ndash;I and SI Appendix Fig. S18). These findings indicate that \u003cem\u003eNfe2l1\u003c/em\u003e deficiency drives selective loss of Type IIb fibers and a phenotypic shift toward Type IIa and Type I fiber populations in KO mice by 20 weeks of age.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEarly-onset molecular and ultrastructural dysregulation in 4-week-old KO SkM without overt pathological phenotypes.\u003c/b\u003e The earlier pathological findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and SI Appendix Fig. S10) indicated minimal impact on the SkM of 4-week-old KO mice. To further validate the effect of \u003cem\u003eNfe2l1\u003c/em\u003e deletion at this age, we collected muscle tissues (Supplementary Fig. S19) and analyzed organ coefficients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), observing no significant differences between genotypes. Consistent with the 20-week-old cohort, analyses of inflammation-related markers (Supplementary Fig. S20) in SkM tissues revealed no significant changes in 4-week-old KO mice, suggesting that \u003cem\u003eNfe2l1\u003c/em\u003e deletion did not induce notable muscle pathologies at this early stage. Immunofluorescence staining also showed no alterations in muscle fiber type composition (Supplementary Fig. S21).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDespite the absence of overt pathological phenotypes, ultrastructural analysis of quadriceps muscles unveiled striking subcellular abnormalities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In KO mice, sarcomere structures were damaged, with blurred cross-striations, twisted or fragmented Z lines (or even Z-line loss), and disorganized myofilament arrangement. Mitochondria exhibited significantly increased cristae density but disordered organization, often forming concentric or fingerprint-like aggregates, hallmarks of chronic energy stress. Additionally, outer mitochondrial membrane rupture with content release and marked dilation of the sarcoplasmic reticulum lumen into vesicular or balloon-like structures, accompanied by myofibril hyperextension, were observed. These ultrastructural defects suggest early-onset dysfunction in contractile and bioenergetic machinery.\u003c/p\u003e\u003cp\u003eDifferential proteomic analysis of calf muscles identified 39 significantly downregulated, 182 upregulated, and 1,656 unchanged proteins in KO mice (Supplementary Fig. S22A). GSEA revealed significant suppression of the proteasome, KEAP1-NFE2L2 axis, and organic acid catabolic pathways in the KO muscle, while upregulated pathways were enriched in cell stress responses, including antigen processing/presentation (APP), HSF1-mediated heat shock response (HSR), oxidative stress-induced senescence, and apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Downregulated proteins were predominantly associated with the UPS, including proteasome subunits (ADRM1, PSMA1)(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), NPL4 homolog, ubiquitin recognition factor (NPLOC4) and NSFL1 (p97) cofactor (p47) (NSFL1C)(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and SI Appendix Fig. S22B). Upregulated proteins were linked to ER stress (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), apoptosis (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), and cellular senescence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and SI Appendix Fig. S22C), indicating a coordinated stress response to UPS dysfunction.\u003c/p\u003e\u003cp\u003eUntargeted metabolomics further revealed metabolic dysregulation in KO muscle. Orthogonal partial least squares discriminant analysis (OPLS-DA) distinguished metabolic profiles between Flox and KO groups (Supplementary Fig. S22D), with metabolite set enrichment analysis (MSEA) identifying six altered pathways: gluconeogenesis, lactose degradation, sphingolipid metabolism, glucose\u0026ndash;alanine cycle, pyruvate metabolism, and glycerolipid metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE\u0026ndash;F and SI Appendix Fig. S22E\u0026ndash;F). Levels of malic acid and alanine were significantly elevated, while MG(0:0/16:0) and D-glucose were reduced in KO mice. Targeted lipidomics confirmed a reduction in monohexosylceramide (Hex1Cer), a sphingolipid critical for membrane integrity/signaling(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) as well as increase in glycerolipids (triglycerides [TG], diacylglycerols [DG]) in KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG and SI Appendix Figs. S22G\u0026ndash;I), suggesting impaired lipolysis consistent with NFE2L1\u0026rsquo;s role in regulating adipocyte lipolytic enzymes(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eUnveiling the cellular and molecular landscape of 4-week-old\u003c/b\u003e \u003cb\u003eNfe2l1\u003c/b\u003e\u003cb\u003e(SM)-KO mice via snRNA-seq.\u003c/b\u003e\u0026nbsp;To achieve high-resolution characterization and further validate the cellular and molecular mechanisms underlying early-stage (4-week-old) SkM structural and metabolic alterations in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice, we performed snRNA-seq on calf muscle tissue. Dimensionality reduction and clustering analysis identified 24 distinct cell clusters (labeled 0\u0026ndash;23, Supplementary Fig. S23). Based on marker gene analysis, we identified 12 major nuclear populations that encompassed all typical cell types found in SkM tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B and Supplementary Fig. S24A-L, Table S9). These included five types of multinucleated myofiber nuclei, namely type I (\u003cem\u003eMyh7\u003c/em\u003e), IIa (\u003cem\u003eMyh2\u003c/em\u003e), IIx (\u003cem\u003eMyh1\u003c/em\u003e), IIb (\u003cem\u003eMyh4\u003c/em\u003e), and myotendinous junction fibers (MTJ, \u003cem\u003eCol22a1\u003c/em\u003e), as well as seven mononuclear cell types, including adipogenic progenitor cells (APC, \u003cem\u003eApod\u003c/em\u003e), endothelial cells (EC, \u003cem\u003ePecam1\u003c/em\u003e), fibro-adipogenic progenitors (FAP, \u003cem\u003eDcn\u003c/em\u003e), immune cells (IC, \u003cem\u003ePtprc\u003c/em\u003e), satellite cells (SC, \u003cem\u003ePax7\u003c/em\u003e), smooth muscle cells (SMC, \u003cem\u003eMyh11\u003c/em\u003e), and tenocytes (Teno, \u003cem\u003eMkx\u003c/em\u003e)(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Using Single-Cell rEgulatory Network Inference and Clustering (SCENIC)(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), we identified five relatively specific regulons for these 12 nuclear types, further confirming the accuracy of our cell type annotation (Supplementary Fig. S24M). For example, the activity scores of ESRRG(+) and PPARGC1A(+), key regulators of mitochondrial biogenesis and function(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), were higher in type I, IIa, and IIx myonuclei than in other nuclear types, such as IIb, MTJ, and non-myonuclei (Supplementary Fig. S24M). Nuclear composition analysis showed that type IIb myonuclei were predominant in both Flox and KO groups, accounting for 61.71% and 61.75%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, right panel). Notably, in the KO mice, the proportions of FAP and IC were increased, suggesting that early muscle fiber damage may induce IC aggregation and abnormal proliferation of FAP(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next performed DEA between Flox and KO groups for all five myonuclear types and then focused on the three main myonuclear populations (IIb, IIx, and IIa), since MTJ and type I comprised a small fraction and showed few differentially expressed genes (DEGs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and Supplementary Fig. S25A). Venn analysis of downregulated and upregulated genes in IIb, IIx, and IIa myonuclei revealed the presence of overlapping downregulated and upregulated genes, with greater overlap among upregulated genes (Supplementary Fig. S25B-C). Functional enrichment analysis of downregulated genes demonstrated that IIb myonuclei were mainly enriched in the UPS, muscle development, and hypertrophy pathways; IIx myonuclei were primarily associated with the UPS, mitochondrial fusion, and adaptive thermogenesis; IIa myonuclei were mainly enriched in adaptive thermogenesis and cellular responses to oxygen levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Functional enrichment analysis of upregulated genes indicated that IIb, IIx, and IIa myonuclei were all significantly enriched in oxidative stress and apoptosis-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Volcano plots of DEGs in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC highlighted representative downregulated genes involved in the UPS, such as proteasome subunit \u003cem\u003ePsmd1\u003c/em\u003e, ubiquitin ligase \u003cem\u003eNedd4l\u003c/em\u003e(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and ubiquitin substrate transporter \u003cem\u003eVcp\u003c/em\u003e(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), and mitochondrial pathways, including mitochondrial protein quality control regulator \u003cem\u003eAfg3l2\u003c/em\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) and master mitochondrial biogenesis regulator \u003cem\u003ePpargc1a\u003c/em\u003e, as well as upregulated genes involved in cellular stress (\u003cem\u003eTxnip\u003c/em\u003e, \u003cem\u003eHspb1\u003c/em\u003e)(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and apoptosis (\u003cem\u003eTpt1\u003c/em\u003e, \u003cem\u003eGsdme\u003c/em\u003e)(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Notably, \u003cem\u003eTxnip\u003c/em\u003e and \u003cem\u003eTpt1\u003c/em\u003e were among the top 20 upregulated genes in all three myonuclear types of the KO mice (Supplementary Fig. S25D-F). These transcriptional and pathway changes largely matched the proteomics results (decreased UPS, increased stress and apoptosis pathways), also suggesting that \u003cem\u003eNfe2l1\u003c/em\u003e deletion exerts relatively specific effects on the function of different myonuclear types that are closely related to their metabolic profiles.\u003c/p\u003e\u003cp\u003eTo further explain the significant changes in metabolites observed in the KO mice, including glycogen accumulation (Supplementary Fig. S25G) and elevated malic acid, triglyceride, and alanine levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-G), we systematically screened for metabolism-related, downregulated genes in the three major myonuclear types (IIb, IIx, and IIa) of KO mice (Supplementary Fig. S25H). Some genes, such as \u003cem\u003ePnpla3\u003c/em\u003e, \u003cem\u003ePhka1\u003c/em\u003e, and malic enzyme 1 (\u003cem\u003eMe1\u003c/em\u003e), showed particularly marked downregulation (Supplementary Fig. S25D-F). By integrating Reactome(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) pathway information, we constructed a schematic diagram of key metabolic reactions to illustrate the relationship between transcriptional changes and metabolic abnormalities (Supplementary Fig. S25I). Specifically, the glycogenolysis-related genes \u003cem\u003ePhka1\u003c/em\u003e, \u003cem\u003ePhkb\u003c/em\u003e, and \u003cem\u003ePhkg1\u003c/em\u003e(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) were significantly downregulated in the KO group, indicating compromised glycogen breakdown capacity in SkM, which was consistent with PAS staining (Supplementary Fig. S25G). In addition, \u003cem\u003eMe1\u003c/em\u003e, a gene encoding an enzyme that catalyzes the conversion of malate to pyruvate(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), also exhibited downregulated expression in the myonuclei of KO mice relative to the Flox group, suggesting that \u003cem\u003eNfe2l1\u003c/em\u003e deficiency may impair energy metabolism efficiency in muscle fibers. For lipid metabolism, low expression of \u003cem\u003ePnpla3\u003c/em\u003e may partly explain the accumulation of triglycerides (TG) and diacylglycerol (DG) and the decrease in monoacylglycerol (MG) observed in KO SkM (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-G). In terms of amino acid metabolism, glutamate-pyruvate transaminase 2 (GPT2), a key enzyme mediating the reversible conversion between alanine and pyruvate(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), exhibited downregulation in KO mice, which suggests a reduction in the connectivity between nitrogen and energy metabolism. In addition, apart from the aforementioned decreased cAMP signaling (\u003cem\u003ePde4b\u003c/em\u003e, \u003cem\u003ePde4d\u003c/em\u003e) and adaptive thermogenesis (\u003cem\u003ePpargc1a\u003c/em\u003e, \u003cem\u003eEsrrg\u003c/em\u003e) pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and Supplementary Fig. S25H), \u003cem\u003eNfe2l1\u003c/em\u003e ablation also led to significant downregulation of other important metabolic and signaling regulators, such as energy-sensing genes (\u003cem\u003ePrkaa2\u003c/em\u003e, \u003cem\u003ePrkag3\u003c/em\u003e)(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) and glucocorticoid response (\u003cem\u003eNr3c1\u003c/em\u003e)(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnalysis of intergroup differential regulon activity based on the SCENIC further supported the above findings: the activity of STAT5B(+), a regulator of growth factor signaling(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) and NR3C1(+) was significantly decreased in the three types of myonuclei of KO mice, while ESRRG(+) and PPARGC1A(+) activity was significantly reduced in IIx and IIa myonuclei; four regulons related to mitochondrial stress, autoimmunity, and inflammation(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), including IRF7(+), IRF8(+), JUND(+), and ETS2(+), showed marked increases in all three types of myonuclei in KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE and Supplementary Fig. S26A-H). To clarify which downregulated genes could be directly attributed to NFE2L1 regulation, we integrated four publicly available NFE2L1 ChIP-seq datasets, identifying 706 high-confidence downstream target genes. Subsequent pathway analysis revealed that the top five pathways were all closely related to the UPS (Supplementary Fig. S27A-D). Overlapping these 706 genes with the 437 significantly downregulated genes across five myonuclear types in KO mice identified 33 downregulated genes that could be directly attributed to \u003cem\u003eNfe2l1\u003c/em\u003e deletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF and Supplementary Fig. S27E-J). These genes were mainly involved in the UPS, including proteasome subunit genes (\u003cem\u003ePSMA3\u003c/em\u003e, \u003cem\u003ePSMD1\u003c/em\u003e), E3 ubiquitin ligase (\u003cem\u003eRffl\u003c/em\u003e)(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), ubiquitinated substrate transport (\u003cem\u003eVcp\u003c/em\u003e, \u003cem\u003eNploc4\u003c/em\u003e), and mitochondrial protein quality control (\u003cem\u003eAfg3l2\u003c/em\u003e). Although the network is not exhaustive, these results collectively emphasize the central role of NFE2L1 in the SkM fiber proteostasis regulatory system.\u003c/p\u003e\u003cp\u003eCell-cell communication analysis revealed that both overall communication strength and the number of interactions were decreased in KO mice, but signaling involving IC was significantly increased, particularly between IC and FAP, SC, and APC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG and Supplementary Fig. S28A-C). Among all signaling pathways, the insulin-like growth factor 1 (IGF1)-insulin-like growth factor 1 receptor (IGF1R) axis was the most prominent (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH and Supplementary Fig. S28D-E), hinglighting its critical role in mediating alterations in the SkM micro-environment in KO mice.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRescue of\u003c/b\u003e \u003cb\u003eNfe2l1\u003c/b\u003e\u003cb\u003e(SM)-KO phenotypes by rolipram treatment.\u003c/b\u003e To investigate whether enhancing proteasome function via a posttranslational mechanism could alleviate the phenotypes in KO mice, we employed rolipram, a phosphodiesterase 4 (PDE4) inhibitor, in rescue experiments. Four-week-old male KO mice were treated with rolipram (2 mg/kg BW) or vehicle (saline) for 21 days respectively. Although no significant intergroup differences were observed in body weight, macroscopic appearance, or organ coefficients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, C and Supplementary Fig. S29A), running-wheel exercise testing revealed a\u0026thinsp;~\u0026thinsp;2-fold reduction in shock frequency, a surrogate marker of improved exercise tolerance, in rolipram-treated KO mice, approaching statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.052; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Histological analysis of quadriceps and gastrocnemius muscles demonstrated marked improvements in rolipram-treated KO mice compared to vehicle controls. The rolipram-treated mice exhibited well-preserved muscle fiber boundaries, intact sarcomeric structures, and reduced basophilic staining, indicative of decreased inflammation or cellular stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI, left panels and Supplementary Fig. S29B). Notably, macrophage infiltration was significantly diminished in rolipram-treated KO muscle (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI, right panels). Immunohistochemical staining for the macrophage marker F4/80 further supported the anti-inflammatory effect of rolipram in the KO mice, with treated KO mice exhibiting a substantial reduction in F4/80\u003csup\u003e+\u003c/sup\u003e cell infiltration compared to vehicle controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI\u0026ndash;J and Supplementary Fig. S29C). A bulk RNA-seq analysis identified 169 downregulated and 76 upregulated genes in rolipram-treated vs. vehicle KO mice, with key inflammatory genes (\u003cem\u003eNlrp3\u003c/em\u003e, \u003cem\u003eNfkbiz\u003c/em\u003e) among the most significantly suppressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). GSEA confirmed reduced enrichment of inflammatory response and leukocyte activation pathways, while upregulated processes included C-terminal protein modification and carbohydrate catabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Gene set variation analysis (GSVA) revealed enhanced ubiquitin-dependent protein catabolism via the C-end degron pathway and diminished negative regulation of antigen-induced inflammation in rolipram-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF\u0026ndash;G). RT-qPCR validation showed a consistent downward trend in inflammation-related transcripts (\u003cem\u003eAdgre1\u003c/em\u003e, \u003cem\u003eCd68\u003c/em\u003e, \u003cem\u003eCasp1\u003c/em\u003e) following rolipram treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). Together, these results demonstrate that rolipram partially rescues skeletal muscle pathology in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice by restoring proteasome-dependent protein homeostasis, highlighting the therapeutic potential of PDE4 inhibition in NFE2L1-associated myopathies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn-depth analysis of Type IIb myonuclei reveals distinct subpopulations and potential myonuclei transitions in\u003c/b\u003e \u003cb\u003eNfe2l1\u003c/b\u003e\u003cb\u003e(SM)-KO mice.\u003c/b\u003e To further investigate the alterations of type IIb myonuclei, the most abundant and most significantly affected population in KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and D), we performed a systematic analysis of subpopulations within type IIb myonuclei (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Composition analysis revealed that type IIb myonuclei could be further divided into seven subpopulations: 0, 1, 2, 3, 5, 6, and 13 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The distribution of these subpopulations differed significantly between the Flox and KO mice: subpopulations 5 and 6 were markedly reduced in KO mice, while subpopulation 1 and the scarcely present subpopulation 13 in Flox mice were dramatically increased in KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, right panel and SI Appendix, Table S10). We next identified a total of 2,815 subpopulation-specific characteristic genes, with subpopulation 5 harboring the largest number (722 genes), suggesting its functional diversity and complexity, while subpopulation 0 had the fewest characteristic genes (46 genes) (Supplementary Fig. S30A). K-means clustering was then applied to further group the subpopulations and their characteristic genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB), and the top 50 characteristic genes of each subpopulation were visualized as bubble plots (Supplementary Fig. S30B-H). The results showed that subpopulations 5 and 6 shared highly similar transcriptional profiles, whereas subpopulation 13 was markedly distinct from the others.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we performed trajectory inference to characterize the potential transition fates of these myonuclei. First, RNA velocity analysis(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) was used to unbiasedly estimate the directionality of nuclear transitions (Supplementary Fig. S31A), followed by Monocle3 pseudotime trajectory analysis(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). The results revealed that only a single transition path existed in the Flox group (the grey points indicated undetermined states in the Monocle3 pipeline); similar to aerobic exercise, type IIb myonuclei could convert toward IIx and IIa types (blue dashed line). In contrast, two potential trajectories emerged in KO mice: one mirroring Flox mice, with conversion toward IIx myonuclei (blue dashed line); the other involving transitions among subpopulations 5, 1, and 13 (red dashed line).\u003c/p\u003e\u003cp\u003eTo further elucidate the state, function, and key mechanisms underlying the aberrant transitions (red trajectory) in the KO group, we performed functional enrichment analysis of all characteristic genes for each subpopulation (excluding subpopulation 0 due to the small number of characteristic genes; Supplementary Fig. S31B-G). The main enriched pathways were then subjected to pathway scoring, allowing for systematic comparison among subpopulations and between genotypes (subpopulation 13 in the Flox group was not included in comparisons due to its low abundance\u0026mdash;24 nuclei, 0.33%; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and Supplementary Fig. S32A-P). The results showed that, compared to the other subpopulations, subpopulations 5 and 6 were most prominent in terms of proteasomal protein catabolic process (\u003cem\u003eSh3rf2\u003c/em\u003e, \u003cem\u003eNedd4l\u003c/em\u003e), muscle system process (\u003cem\u003eCtnna3\u003c/em\u003e, \u003cem\u003ePde4d\u003c/em\u003e), muscle hypertrophy (\u003cem\u003eSorbs2\u003c/em\u003e, \u003cem\u003eIgfbp5\u003c/em\u003e), regulation of Wnt signaling pathway (\u003cem\u003eCbfb\u003c/em\u003e, \u003cem\u003eGpc5\u003c/em\u003e), muscle adaptation (\u003cem\u003eFbxo32\u003c/em\u003e, \u003cem\u003eFoxo3\u003c/em\u003e), insulin-like growth factor receptor signaling pathway (\u003cem\u003eIgfbp5\u003c/em\u003e, \u003cem\u003eGhr\u003c/em\u003e), rhythmic process (\u003cem\u003eRora\u003c/em\u003e, \u003cem\u003eDdx5\u003c/em\u003e), response to insulin (\u003cem\u003ePnpla3\u003c/em\u003e, \u003cem\u003eStxbp4\u003c/em\u003e), and cAMP metabolic process (\u003cem\u003ePde4d\u003c/em\u003e, \u003cem\u003ePde4b\u003c/em\u003e), with subpopulation 5 being the most significant ( Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and Supplementary Fig. S32-L). Notably, the UPS pathway scores (i.e., proteasomal protein catabolic process) were significantly lower in KO mice across all subpopulations (Supplementary Fig. S32B).\u003c/p\u003e\u003cp\u003eWe next focused on subpopulations 1 and 13, which were dramatically increased in KO mice. The top 50 characteristic genes of subpopulation 1 displayed characteristics of both subpopulation 5 (\u003cem\u003eCtnna3\u003c/em\u003e, \u003cem\u003eLrrtm3\u003c/em\u003e) and subpopulation 13 (\u003cem\u003eMyl1\u003c/em\u003e, \u003cem\u003eDmd\u003c/em\u003e, \u003cem\u003eFlnc\u003c/em\u003e, \u003cem\u003eCamk2d\u003c/em\u003e), and were grouped together by K-means clustering (Supplementary Fig. S30F), consistent with the trajectory inference, further supporting that subpopulation 1 represents an intermediate state of transition from subpopulation 5 to subpopulation 13. Pathway scoring showed that key functional signatures, UPS, muscle system process, and response to insulin, were all lower in subpopulation 1 compared to subpopulation 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and Supplementary Fig. S32A, C and I). Between genotypes, the KO mice exhibited even lower UPS, rhythmic process, and cAMP metabolic process scores in subpopulation 1 (Supplementary Fig. S32B, H and L). These scores further declined in subpopulation 13, which meanwhile possessed the highest scores for stress and apoptosis-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and Supplementary Fig. S32A-P).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCross-species comparison of conserved molecular features between\u003c/b\u003e \u003cb\u003eNfe2l1\u003c/b\u003e\u003cb\u003e(SM)-KO mice and aging-associated type II myonuclear subpopulations in humans.\u003c/b\u003e Lai et al.(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e) recently constructed multimodal cell atlas of the aging human SkM and identified multiple myonuclear subpopulations closely associated with aging. Among the myonuclei analyzed, aged individuals exhibited either significant increases or an upward trend in \u0026ldquo;typical\u0026rdquo; Type I myonuclei (representing the largest cluster among all Type I myonuclei, and defined independently of the positivity for other genes), \u003cem\u003eDCLK1\u003c/em\u003e⁺(I), \u003cem\u003eID1\u003c/em\u003e⁺(I), \u003cem\u003eSAA2\u003c/em\u003e⁺(I), \u003cem\u003eTNNT2\u003c/em\u003e⁺(I), \u003cem\u003eDCLK1\u003c/em\u003e⁺(II), \u003cem\u003eID1\u003c/em\u003e⁺(II), \u003cem\u003eSAA2\u003c/em\u003e⁺(II), and \u003cem\u003eTNNT2\u003c/em\u003e⁺(II) (Appendix, Fig. S33A-D)(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Conversely, \u0026ldquo;typical\u0026rdquo; Type II myonuclei, the largest cluster among all Type II myonuclei defined independently of other marker genes, and \u003cem\u003eENOX1\u003c/em\u003e⁺(II) myonuclei both showed significant age-related decreases (Appendix, Fig. S33A-D). Notably, they pointed out that \u003cem\u003eTNNT2\u003c/em\u003e⁺, \u003cem\u003eDCLK1\u003c/em\u003e⁺, \u003cem\u003eID1\u003c/em\u003e⁺, and \u003cem\u003eSAA2\u003c/em\u003e⁺ myonuclei were associated with one or multiple adverse outcomes, including denervation, aging(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), dystrophic repair(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), inflammation, and chronic tissue injury responses(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). \u003cem\u003eENOX1\u003c/em\u003e⁺ myonuclei, on the other hand, likely represent healthy type II fibers, characterized by high expression of genes related to carbohydrate metabolism and circadian rhythm regulation(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo investigate the common patterns of metabolic state and fate transition for mouse subpopulations 5 and 13, and assess their evolutionary conservation in humans, we performed a cross-species comparison of different type II myonuclear subpopulations. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA shows the UMAP of type II myonuclei from the Lai\u0026rsquo;s dataset, colored by subpopulation annotation (left), age group (middle), and \u003cem\u003eENOX1\u003c/em\u003e expression (right). Of the top 50 characteristic genes of mouse subpopulation 5, 40 orthologues were found in Lai\u0026rsquo;s dataset after conversion to human orthologous genes (Supplementary Fig. S33E-F). K-means clustering revealed that \u003cem\u003eENOX1\u003c/em\u003e⁺ (II) and \u0026ldquo;typical\u0026rdquo; Type II grouped together. Furthermore, compared to the other four type II myonuclear subpopulations (labeled in red), genes such as \u003cem\u003eMACROD2\u003c/em\u003e, \u003cem\u003ePDE4D\u003c/em\u003e, and \u003cem\u003ePHKA1\u003c/em\u003e were expressed at significantly higher levels in \u003cem\u003eENOX1\u003c/em\u003e⁺ (II) subpopulation. Notably, the top characteristic gene for mouse subpopulation 5 was \u003cem\u003eEnox2\u003c/em\u003e, a paralog of \u003cem\u003eEnox1\u003c/em\u003e, whereas \u003cem\u003eENOX2\u003c/em\u003e lacked high expression in any human type II myonuclear subpopulations (Supplementary Fig. S33F).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo more intuitively assess the relationship between human type II myonuclear subpopulations and mouse subpopulation 5, we calculated gene set scores based on the 40 orthologues and defined as subpopulation characteristic scores or myonuclear characteristic scores. Both \u003cem\u003eENOX1\u003c/em\u003e⁺(II) and \u0026ldquo;typical\u0026rdquo; Type II received the highest and second highest scores, respectively, with \u003cem\u003eENOX1\u003c/em\u003e⁺(II) scoring significantly higher than \u003cem\u003eSAA2\u003c/em\u003e⁺ (II) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Similarly, among the top 50 characteristic genes of human \u003cem\u003eENOX1\u003c/em\u003e⁺ (II), 33 homologous genes were detectable in the mouse dataset (Supplementary Fig. S33G-H). K-means clustering showed that mouse subpopulations 5 and 6 grouped together, both of which showed markedly higher expression of various \u003cem\u003eENOX1\u003c/em\u003e⁺(II) characteristic genes, though \u003cem\u003eEnox1\u003c/em\u003e itself was scarcely expressed across all mouse subpopulations (Supplementary Fig. S33H). Characteristic score analysis further demonstrated that subpopulations 5 and 6 had the highest and second highest scores, while subpopulation 13 scored the lowest (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eUsing a similar approach, we then calculated characteristic scores based on the top 50 characteristic genes from mouse subpopulation 13 and human \u003cem\u003eID1\u003c/em\u003e⁺(II) myonuclei with 45 and 42 orthologous genes, respectively (Supplementary Fig. S33I-L). The results showed that human \u003cem\u003eDCLK1\u003c/em\u003e⁺(II) and \u003cem\u003eID1\u003c/em\u003e⁺(II) had the highest and second highest subpopulation 13 characteristic scores, followed by \u003cem\u003eSAA2\u003c/em\u003e⁺ (II), and all these subpopulations scored significantly higher than \u003cem\u003eENOX1\u003c/em\u003e⁺(II) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). In mice, subpopulation 13 and subpopulation 2 had the highest and second highest \u003cem\u003eID1\u003c/em\u003e⁺(II) characteristic scores, respectively, followed by subpopulation 1, all significantly above subpopulation 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eWe further summarized the overlapping characteristic genes between human \u003cem\u003eENOX1\u003c/em\u003e⁺(II) myonuclei and mouse subpopulation 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF and Supplementary Fig. S33M, marked in blue), as well as characteristic genes shared by mouse subpopulation 13 and one or more of the human \u003cem\u003eDCLK1\u003c/em\u003e⁺(II), \u003cem\u003eID1\u003c/em\u003e⁺(II), \u003cem\u003eSAA2\u003c/em\u003e⁺(II), and \u003cem\u003eTNNT2\u003c/em\u003e⁺(II) myonuclei (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF and Supplementary Fig. S33M, marked in red). Collectively, cross-species comparison of type II myonuclear characteristics revealed that mouse subpopulation 5, which is dramatically reduced upon \u003cem\u003eNfe2l1\u003c/em\u003e deletion, shares high functional similarity and substantial molecular overlap with human \u003cem\u003eENOX1\u003c/em\u003e⁺ (II) and \u0026ldquo;typical\u0026rdquo; Type II myonuclei lost during aging. Conversely, the abnormally expanded subpopulation 13 in KO mice resembled aged-enriched human myonuclear states, with considerable concordance in molecular characteristics.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study integrates human genetics, mouse modeling, and multi-omics to establish NFE2L1 as a central regulator of SkM homeostasis. In humans, NFE2L1 ranks among the most SkM-enriched transcription factors, with expression declining in an age-dependent manner, and correlating with sarcopenia severity. UK Biobank analyses revealed robust genetic associations between \u003cem\u003eNFE2L1\u003c/em\u003e variants and appendicular lean mass and hand grip strength, including genome-wide significant loci, underscoring its conserved role in muscle proteostasis. These findings align with co-expression network analyses, which identified enrichment of proteasome subunit genes and ubiquitin-mediated degradation pathways, linking NFE2L1 to the UPS.\u003c/p\u003e\u003cp\u003eSkM-specific deletion of \u003cem\u003eNfe2l1\u003c/em\u003e recapitulated hallmarks of aging, including progressive muscle atrophy, Type IIb fiber loss, and inflammatory response and fat infiltration. Central to these phenotypes is NFE2L1\u0026rsquo;s regulation of UPS function, including KO mice exhibited downregulation of UPS genes and accumulation of ubiquitinated proteins, accompanied by early-onset ultrastructural defects in 4-week-old muscle, such as sarcomeric disorganization, mitochondrial cristae abnormalities, and sarcoplasmic reticulum dilation. Proteomics and metabolomics revealed early metabolic dysregulation, including glycogen accumulation and lipid peroxidation, and activation of ER and oxidative stress pathways, establishing a hierarchical model where \u003cem\u003eNfe2l1\u003c/em\u003e loss initiates UPS impairment, triggering compensatory mitochondrial remodeling and metabolic reprogramming that culminate in cellular stress.\u003c/p\u003e\u003cp\u003eSnRNA-seq unveiled striking heterogeneity within Type IIb myonuclei. In KO muscle, Type IIb subpopulations 5 and 6 characterized by high expression of UPS and metabolic genes were reduced, while stress/RCD-associated subpopulation 13 expanded. Trajectory inference identified two distinct fates for Type IIb fibers, namely oxidative remodeling toward Type IIx/IIa via ESRRG-mediated mitochondrial biogenesis and degenerative transition to subpopulation 13, marked by \u003cem\u003eAtf3\u003c/em\u003e and RCD genes. Cross-species comparisons with human aging muscle revealed conservation of these characteristics, where mouse subpopulation 5 mirrored \u0026ldquo;healthy\u0026rdquo; \u003cem\u003eENOX1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e type II fibers(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), and subpopulation 13 resembled aging-associated \u003cem\u003eID1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e/\u003cem\u003eDCLK1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e type II fibers(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), highlighting NFE2L1\u0026rsquo;s role in preserving functional fiber identity.\u003c/p\u003e\u003cp\u003e\u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice exhibited a pro-inflammatory phenotype, with upregulated macrophage markers (\u003cem\u003eAdgre1\u003c/em\u003e, \u003cem\u003eCd68\u003c/em\u003e) and pyroptosis genes (\u003cem\u003eCasp1\u003c/em\u003e, \u003cem\u003eNlrp3\u003c/em\u003e), and enhanced immune cell-fibroblast communication. Treatment with rolipram, a PDE4 inhibitor, rescued KO phenotypes by enhancing UPS activity via PKA-mediated phosphorylation and suppressing inflammation, reducing F4/80\u003csup\u003e+\u003c/sup\u003e infiltration and restoring muscle architecture. These results align with rolipram\u0026rsquo;s efficacy in tauopathy models(\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) and highlight the therapeutic potential of targeting UPS-inflammation crosstalk in NFE2L1-related myopathies.\u003c/p\u003e\u003cp\u003eThe present study harbors several notable limitations that warrant acknowledgment. First, while NFE2L1 encodes functionally distinct isoforms(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), this research did not delineate the specific roles of these isoforms within SkM, leaving unresolved questions about their differential contributions to proteostasis. Second, the dynamic transitions of myonuclear states across different age strata in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO mice remain uncharacterized, constituting a pivotal knowledge gap in deciphering the spatiotemporal regulatory function of NFE2L1 during SkM aging. Third, the systemic effects of rolipram highlight the need for the development of muscle-targeted PDE4 inhibitors to mitigate off-target impacts. Future investigations focusing on isoform-specific functional dissection, multi-timepoint snRNA-seq, and the design of muscle-targeted therapeutic strategies will undoubtedly deepen our comprehension of the molecular mechanisms underlying SkM aging and inform targeted interventional approaches.\u003c/p\u003e\u003cp\u003eCollectively, our findings establish NFE2L1 as a critical regulator of SkM proteostasis, linking its decline to age-related degeneration through UPS dysfunction, fiber type attrition, and inflammatory stress. The conserved molecular characteristics between KO mice and aged human muscle position NFE2L1 as a therapeutic target for sarcopenia. By integrating genetic, cellular, and translational insights, this study illuminates new pathways for addressing age-related muscle decline.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eDetailed experimental methods, including publicly available RNA-seq and snRNA-seq data mining, CGAS, establishment animal models, analysis of body composition, evaluation of SkM function, protocols for tissue collection, histological examinations, RT-qPCR, Western blot analysis, snRNA-seq data analysis, and statistical analyses, are comprehensively described in the SI Appendix.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnimal Care and Use.\u003c/b\u003e All animal procedures were conducted in strict accordance with the guidelines of the US National Institutes of Health and approved by the Institutional Animal Care and Use Committee of China Medical University (approval number: CMU20231360, Shenyang, China).​ Mice were housed in specific pathogen-free facilities, with a maximum of four animals per cage. The housing environment was maintained under a 12-hour light/dark cycle. The mice were provided \u003cem\u003ead libitum\u003c/em\u003e access to NIH07 chow diet (Jiangsu Xietong BioTech, Nanjing, China) and reverse osmosis water to ensure proper nutrition and hydration.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHistological, Immunohistochemical (IHC), and Immunofluorescence Analyses.\u003c/b\u003e Isolated SkM tissues were fixed in 4% paraformaldehyde, followed by paraffin embedding, sectioning, and staining with H\u0026amp;E, IHC or immunofluorescence as described previously(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Antibodies for F4/80 (c-377009; 1:200; Cell Signaling Technology), ASC/TMS1 (#67824T; 1:1000; CST), MYH7 (BA-D5, 1:50, DSHB), MYH2 (SC-71, 1:50, DSHB), MYH4 (BF-F3, 1:50, DSHB), LAMININ (#11575, 1:50. Abcam) andα-TUBULIN (#7291; 1:1000, Abcam) were used.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBulk RNA-seq.\u003c/b\u003e\u0026nbsp;RNA extraction, library preparation, and sequencing were conducted by Seqhealth Technology Co., Ltd. (Wuhan, China) and Personalbio Technology Co., Ltd. (Shanghai, China). Total RNA was extracted from skeletal muscles using TRIzol Reagent (Invitrogen, cat. no. 15596026), including the calf muscles (consisting of the soleus, and gastrocnemius muscles) in 20-week-old mice and the quadriceps muscles of mice in rescue study.\u003c/p\u003e\u003cp\u003e\u003cb\u003esnRNA-seq Protocol.\u003c/b\u003e Calf muscle samples from three 4-week-old male mice of each genotype were pooled, rinsed with pre-cooled RNase-free saline, minced on ice, and stored at -80\u0026deg;C. Single-nucleus suspension preparation, separation, library construction, and sequencing were performed by Gene Denovo Biotechnology Co. (Guangzhou, China) following established protocols(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eProteomics Experimental Protocol and Data Analysis.\u003c/b\u003e Protein samples were collected from calf muscles of Flox and \u003cem\u003eNfe2l1\u003c/em\u003e(KM)-KO mice, and analyzed for differentially expressed proteins by mass spectrometry at Beijing Proteome Research Center using the methods described previously(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eUntargeted Lipidomics and Metabolomics.\u003c/b\u003e Approximately 10 mg of -80\u0026deg;C frozen calf muscles (consisting of the soleus and gastrocnemius muscles in mice) samples were subjected to pretreatment and subsequent analyses for untargeted lipidomics and untargeted metabolomics, following previously described protocols. Details was described in supporting information.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRolipram Rescue Study Protocol.\u003c/b\u003e Rolipram (HY-16900, MCE) was stored as 50 mg/mL soluble in DMSO. The storage solution is diluted by 100 times using PBS as an application solution. Four-week-old male \u003cem\u003eNfe2l1\u003c/em\u003e(KM)\u003cb\u003e-\u003c/b\u003eKO mice were given rolipram at 2 mg/kg/d by intramuscular injection for 21 consecutive days, followed by metabolic measurements and tissue collection. Control mice were injected with vehicle (PBS). The sample size comprised 7\u0026ndash;8 mice per group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistics.\u003c/b\u003e All statistical analyses were conducted using GraphPad Prism 5 (GraphPad Software, San Diego, CA), with statistical significance defined as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Student\u0026rsquo;s t-tests were used for comparisons between two groups, while one-way or two-way analysis of variance (ANOVA) was applied for multi-group comparisons.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments and funding sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThis research was supported in part by the National Natural Science Foundation of China 82404316 (Z.W), 82020108027 (J.P.), 82173560 (J.F.); Liaoning Provincial Department of Science and Technology 2023JH2/20200159 (Z.W); the Innovation Team Support from China Medical University (CXTD2022004).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eDuring the writing process of this work, the authors utilized Doubao solely to enhance the language only. After employing these tools/services, the authors reviewed and edited the content as necessary and take full responsibility for the content of the publications.We thank all lab members in Dr. J.P. and Dr. Y.X. laboratory, specially Xue Yao and Yihan Li for the participation on this project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLarsson L et al (2019) Aging-Related Loss of Muscle Mass and Function. Physiol Rev 99(1):427\u0026ndash;511\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShur NF et al (2021) Age-related changes in muscle architecture and metabolism in humans: The likely contribution of physical inactivity to age-related functional decline. Ageing Res Rev 68:101344\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBodine SC, Edward F (2020) Adolph Distinguished Lecture. Skeletal muscle atrophy: Multiple pathways leading to a common outcome. 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Nat Methods 6(5):359\u0026ndash;362\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"NFE2L1, Skeletal muscle, Ubiquitin-proteasome system, Proteostasis","lastPublishedDoi":"10.21203/rs.3.rs-7736640/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7736640/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSkeletal muscle (SkM) relies on precise regulation of protein synthesis and degradation for functional integrity, with the ubiquitin-proteasome system (UPS) as a cornerstone of homeostasis. Nuclear factor (erythroid-derived 2)-like 1 (NFE2L1), a conserved CNC-bZIP transcription factor, integrates redox balance and proteasome gene expression, but its fiber-type-specific roles in SkM remain unclear. \u0026nbsp;Here, we integrated multi-omics datasets from aging and sarcopenia cohorts to characterize the spatiotemporal activity of NFE2L1 in SkM. Genetic variants in \u003cem\u003eNFE2L1\u003c/em\u003e were significantly associated with lean muscle mass and grip strength in the UK Biobank. Striated muscle-specific \u003cem\u003eNfe2l1 \u003c/em\u003eknockout mice (\u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO) displayed age-dependent SkM atrophy characterized by preferential loss of Type IIb fibers, heightened inflammatory response, fat infiltration and regulated cell death (RCD). Proteomic, metabolomic, and lipidomic analyses unveiled a NFE2L1-driven regulatory network maintaining UPS function and metabolic homeostasis. Single-nucleus RNA sequencing revealed global UPS dysfunction and shifts in myonuclear states toward RCD-prone phenotypes in \u003cem\u003eNfe2l1\u003c/em\u003e(SM)-KO muscle. Pharmacological activation of proteasomes with rolipram partially mitigated atrophy in juvenile knockouts, and human aging SkM datasets confirmed conserved myonuclear state transitions. Collectively, NFE2L1 emerges as a pivotal spatiotemporal regulator of SkM proteostasis, bridging UPS maintenance with fiber-type integrity and offering therapeutic targets for age-related muscle decline.\u003c/p\u003e","manuscriptTitle":"NRF1/NFE2L1 orchestrates spatiotemporal regulation of protein degradation network in skeletal muscle","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 06:56:36","doi":"10.21203/rs.3.rs-7736640/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":"cc7d479e-bd8c-4c9b-ac13-b5a0f2b2d1a6","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":56053836,"name":"Biological sciences/Cell biology/Cell death"},{"id":56053837,"name":"Biological sciences/Cell biology/Cell signalling"}],"tags":[],"updatedAt":"2025-10-21T06:56:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 06:56:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7736640","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7736640","identity":"rs-7736640","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}