Multiomics mapping and characterization of cellular senescence in aging human skeletal muscle uncovers a novel senotherapeutic for sarcopenia

Multiomics mapping and characterization of cellular senescence in aging human skeletal muscle uncovers a novel senotherapeutic for sarcopenia | 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 Multiomics mapping and characterization of cellular senescence in aging human skeletal muscle uncovers a novel senotherapeutic for sarcopenia Huating Wang, Yang Li, Chuhan Li, Qin Zhou, Xingyuan Liu, Yulong Qiao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5399514/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jul, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Cellular senescence is recognized as a hallmark of organismal aging but how it drives aging particularly in human tissues is not fully understood, partly due to the complex heterogeneous nature of senescence. Here in this study, we leverage single-nucleus multiomics to profile senescence in mononucleated cells of human skeletal muscle and provide the first senescence atlas. We demonstrate the intra- and inter-populational transcriptomic and epigenomic heterogeneity and dynamics of senescence in the cells. We also identify commonalities and variations in senescence-associated secretory phenotypes (SASPs) among the cells and elucidate the function of SASPs in mediating cellular interactions and niche deregulation. Furthermore, we identify targetable SASP factors and demonstrate the possibility of using Maraviroc as a pharmacological senotherapeutic for treating age-associated sarcopenia in muscle. Lastly, we define transcription factors that govern senescence state and SASP induction in aging muscle and elucidate the key function and the underlying mechanism of JUNB in regulating SASP activation in senescent cells. Altogether, our findings demonstrate the prevalence and function of cellular senescence in skeletal muscle and identify a novel pharmacological intervention for sarcopenia. Biological sciences/Cell biology/Senescence Biological sciences/Stem cells/Muscle stem cells Biological sciences/Stem cells/Ageing Health sciences/Health care/Therapeutics/Drug therapy/Molecularly targeted therapy Senescence skeletal muscle aging MuSC SASP senotherapeutics Maraviroc JunB Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplFigures.pdf SupplInfo.pdf Cite Share Download PDF Status: Published Journal Publication published 05 Jul, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5399514","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":376796306,"identity":"71ffe602-9ca7-478d-a9ea-27e200183046","order_by":0,"name":"Huating Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABH0lEQVRIiWNgGAWjYBACAxCRAON9MJDg4QeLFODVwtgA08I4o8JCRrIBpMWAgBYYh5nnTIWNwQG47diBuUTy8wcPd9QyGBw/e/gFb5sEj/H51YkfHhgwyPOLHcCqxXJGmmFD4pnjDAZn8tIsJIFazG683SwBdJjhzNkJWLUY3EgAamk7xmB2IMfMwBCs5ewGkJYEg9u4tKR/hGg5/8bMIBHksBlnN//AryUHZEsNg9mNHOMHB85I8Bjw927Db8uZN4UzEtsO8NjfeGPG2FAhwSNxg3ebRYKBBG6/HE/f8PFnW52cZH+O8ec/BnX2/P1nN9/8UWEjzy+NXQsUHOYBEmwSYLYEWKUEPuUgUAcimD+A2fwHCKkeBaNgFIyCEQYATYBmgs7LaIEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-5474-2905","institution":"Chinese University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Huating","middleName":"","lastName":"Wang","suffix":""},{"id":376796307,"identity":"75af27fc-3a3e-44f4-8793-210d1585bca3","order_by":1,"name":"Yang Li","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Li","suffix":""},{"id":376796308,"identity":"3275c27e-09ee-489b-ae66-d4c28d63e116","order_by":2,"name":"Chuhan Li","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Chuhan","middleName":"","lastName":"Li","suffix":""},{"id":376796309,"identity":"0f921eea-fc9b-4d28-9f2c-251816386518","order_by":3,"name":"Qin Zhou","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Qin","middleName":"","lastName":"Zhou","suffix":""},{"id":376796310,"identity":"0981595b-1b8e-4fac-9873-ef6e2501ea75","order_by":4,"name":"Xingyuan Liu","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Xingyuan","middleName":"","lastName":"Liu","suffix":""},{"id":376796311,"identity":"e386ce24-e18e-4a87-8f0b-c4860e909787","order_by":5,"name":"Yulong Qiao","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Yulong","middleName":"","lastName":"Qiao","suffix":""},{"id":376796312,"identity":"4e0f5e34-1dfd-4720-bd94-8ab16d5629ad","order_by":6,"name":"Ting Xie","email":"","orcid":"","institution":"Hong Kong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Xie","suffix":""},{"id":376796313,"identity":"06566c21-7d76-475c-b7a0-283937ad33bc","order_by":7,"name":"Hao Sun","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Sun","suffix":""},{"id":376796314,"identity":"1c481980-9a73-4365-b705-65efc6f16bd5","order_by":8,"name":"Michael Ong","email":"","orcid":"https://orcid.org/0000-0002-4460-9286","institution":"Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Ong","suffix":""}],"badges":[],"createdAt":"2024-11-06 04:55:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5399514/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5399514/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-61403-y","type":"published","date":"2025-07-05T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71829209,"identity":"365accac-05c5-4edb-80c9-fb98127b6c95","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":192222,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the overall design of the study.\u003c/p\u003e","description":"","filename":"MainFigures1.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/27c6e103cef0604c124e49af.png"},{"id":71829210,"identity":"f9ecf1ff-2efa-4f0f-888b-08c3ce705fb1","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":666191,"visible":true,"origin":"","legend":"\u003cp\u003eMultiomics mapping of senescence atlas in aging human muscle. A Uniform manifold approximation and projection (UMAP) plot showing the 12 (sub)types of muscle resident mononucleated cell populations identified through analyzing snRNA-seq. B Alluvial plot showing the distribution of young and aged cells across each of the above 8 main cell types. Pie plots below showing the relative cell composition between old and young groups across each cell type. C Arc plot showing the degree of responsiveness of each cell type to aging. Augur score is shown to prioritize cell types based on their molecular response to aging). D Boxplot illustrating transcriptional noise in young (Y) vs. aged (A) groups for the indicated cells arranged by decreasing order of A vs. Y ratio. The box represents the interquartile range, the horizontal line in the box is the median. Asterisk indicates statistical significance (Wilcoxon’s rank sum test, adjusted p value \u0026lt; 0.05). E Scatter plots of MuSC, FAP, EC, and MP proportions in each of the young and aged donors. The red lines were fitted by a linear model. Shaded areas around the fitted lines indicate the confidence intervals. Pearson’s correlations for the fitted samples are shown. F-I Senescence atlas: UMAP plot colored by SenMayo ss-GSVA score. UMAP plot showing senescent (Sn) vs. non-senescent (nSn) cells of MuSCs, FAPs ECs and SMCs. Bar plot showing the relative ratio of Sn vs. nSn cells between young and aged groups of each cell type. J Dot plot showing representative GO terms of upregulated DEGs in Sn cells across the four cell types. K Schematic of the experimental design for senescence detection in human muscle or freshly isolated MuSCs from additional pairs of young and aged donors. L H\u0026amp;E staining showing the muscle atrophy in aged vs. young human muscle. Quantification of cross-section areas (CSAs) are shown on the right. Scale bar: 50 μm, n=4. M IF staining of DAPI (blue), P16 (green) and P21 (red) was performed on the collected human muscle sections. The percentage of P16+ and P21+ cells is shown on the right. Scale bar: 50 μm, n=3. N MuSCs were freshly isolated from the young and aged muscles and SA-β-GAL staining was performed. The percentage of SA-β-GAL+ cells is shown on the right. Scale bar: 50 μm, n=3. O IF staining of DAPI (blue), P16 (green) and PAX7 (red) was performed on the above isolated and the percentage of P16+ cells is shown on the right. Scale bar: 50 μm, n=3. P RT-qPCR detection of the mRNA expression of P14, P16, P19 and P21 genes in the above MuSCs. n=5. All the bar graphs are presented as mean + SD, Student’s t-test was used to calculate the statistical significance (D, L-P): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, n.s. = no significance.\u003c/p\u003e","description":"","filename":"MainFigures2.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/b0b7aec21a4531d7fbcc5152.png"},{"id":71830161,"identity":"b411bc6b-0696-4b4b-a428-e369a7d36582","added_by":"auto","created_at":"2024-12-19 02:32:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":885493,"visible":true,"origin":"","legend":"\u003cp\u003eHeterogeneity and dynamics of cellular senescence in aging human muscle. A-D Discriminative dimensionality reduction (DDR) tree visualization of MuSC trajectory with mapping of pseudotime (A), age group (B), senescence annotation (C), and CDKN1A expression level (D) information. E Plot showing the ss-GSVA score of cell cycle activity signature along MuSC aging trajectory psuedotime. The solid yellow line is the local regression result for individual pseudotime bins (55 total, sized 0.10 per bin), with the gray shadow depicting the 95% confidence intervals (CIs). F Heat map visualization of expression levels of genes (right) with correlated expression profiles to MuSC aging pseudotime ordered from Early to Late stage. Left: row annotation showing the functions of the genes. G Heat map visualization of expression levels of DEGs between Late 1 and Late 2 fates ordered by pseudotime. H-I DDR tree visualization of FAP trajectory with mapping of pseudotime (H) and senescence annotation (I). J Plot showing the ss-GSVA score of cell cycle activity signature along FAP aging trajectory psuedotime. K Heat map visualization of expression levels of genes with correlated expression profiles to FAP aging pseudotime from Early to Late stage. L-M DDR tree visualization of EC trajectory with mapping of pseudotime (L) and senescence annotation (M). N Plot showing the ss-GSVA score of cell cycle activity signature along EC aging trajectory. O Heat map visualization of expression levels of genes with correlated expression profiles to EC aging pseudotime. P-Q DDR tree visualization of SMC trajectory with mapping of pseudotime (P) and senescence annotation (Q). R Plot showing the ss-GSVA score of cell cycle activity signature along SMC aging trajectory. S Heat map visualization of expression levels of genes with correlated expression profiles to SMC aging pseudotime.\u003c/p\u003e","description":"","filename":"MainFigures3.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/b0eecc18e8bfa7814bd919d8.png"},{"id":71829212,"identity":"03f760d1-0425-47f3-8e03-027b1b2deed6","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":262128,"visible":true,"origin":"","legend":"\u003cp\u003eSASP profiling and function in senescent cells. A Circos plots showing up-regulated and down-regulated DEGs in senescent MuSCs, FAPs, ECs, or SMCs (total numbers indicated in the brackets). Each connecting curve represents an up- or down-regulated Sn-DEG shared by two cell types; light and dark grey arc (inner circle) indicates cell type-unique and shared Sn-DEG, respectively B Upset plot showing the numbers of cell type-unique and shared up-regulated SASP genes for pairwise comparisons among the indicated cell types. C Plot showing the up-regulated SASPs shared by at least two cell types. D Scatter Plot showing the up-regulated SASPs specific in each cell type. E-F Ridge map showing the distribution density of ss-GSVA score for classical SASP genes in the senescent (Sn) vs. non-senescent (nSn) cells (E), as well as aged vs. young cells (F). The dashed line corresponds to the peak position of each group. G-H Heatmap of top-ranked up-regulated SASPs in Sn vs. nSn cells (G), as well as aged vs. young cells (H). I RT-qPCR detection of the expression level of top-ranked up-regulated SASP genes between aged and young human MuSCs, n=5. J Bar plot comparing the interaction strength of SASP-mediated intercellular communications in aged vs. young group. K Heatmap showing differential number of SASP-mediated interactions between two cell types. Red/Blue represents increased/decreased signaling in the aged vs. young. The colored bar plot on the top or right represents the incoming/outgoing signaling setting each cell type as receptor/sender (sum of column/row of displayed values). L Relative flows of differentially active signaling pathways during muscle aging, annotated with their respective functions. M Plot showing the signal strength change by aggregating all L-R pairs within CXCL pathway. The edge color corresponds to the sender cell type, and the edge weight is proportional to the interaction strength. N-O Chord diagram visualizing MuSC-centered cell-cell communication for a set of up-regulated SASP ligands/receptors, with MuSCs designated as the receptor (N) or sender (O) cell type. The edge color corresponds to the sender cell type, and the edge weight is proportional to the interaction strength. P Dot plot showing the increased SASP L-R pairs from MuSC (sender cell) to other cells (target cell) in aged vs. young group. The dot color and size represent the computed communication probability and p-values. Student’s t-test was used to calculate the statistical significance (E-F): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, n.s. = no significance.\u003c/p\u003e","description":"","filename":"MainFigures4.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/4e750702f0c88372c90ee2c2.png"},{"id":71829214,"identity":"036d0271-9cd9-4c1d-a307-67b1095bc016","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":423806,"visible":true,"origin":"","legend":"\u003cp\u003eMaraviroc is a potential senotherapeutic for sarcopenia. A snRNA-seq analysis of the expression of CCL3, CCL4, CCL5 and CCR5 (CCR5 axis genes) in human MuSCs. B RT-qPCR detection of the expression level of CCR5 axis genes in MuSCs freshly isolated from additional pairs of young and aged donors, n=5. C Schematic of high dose short term (HDST) treatment/assessment regime of DMSO or MVC in aging mice, n=8. D The ratio of TA/body weight of the above-treated mice, n=8. E Left: H\u0026amp;E staining of tibialis anterior (TA) muscles collected from the above-treated mice. Right: Quantification of CSAs of the stained fibers, Scale bar: 50 μm, n=6. F-G The treated mice were subjected to a grip strength meter, the final strength and strength changes were measured, n=8. H-I The treated mice were subjected to treadmill exercise and the maximal running speed and distance were recorded, n=8. J Flow cytometry detection of MuSC, MP, and FAP populations in treated mice, n=8. K scRNA-seq was performed on the mononucleated cells isolated from three pairs of DMSO/MVC-treated mice. Unsupervised clustering resolved at least 13 cell types (color-coded). L Top: Sankey plots showing the distribution of DMSO and MVC cells across each cell type. Bottom: pie plots showing the relative proportion of each cell type between DMSO and MVC groups. M-P Top: Bar plot showing the USS-defined relative percentage of senescent vs. non-senescent MuSCs, FAPs, ECs and SMCs in DMSO vs. MVC. Bottom: Violin plot showing the relative expression level of p21 in the cells. Q Bar plot showing SASP-mediated interaction strength of DMSO vs. MVC calculated by CellChat. R Heatmap showing the SASP-mediated cell-cell interaction pairs between two cell types altered between MVC vs. DMSO treatment. The red/blue color indicates the increased or decreased interaction, respectively. S Interaction frequency of Ccl3-Ccr5 and Ccl4-Ccr5 pairs was analyzed in MVC vs. DMSO group. T RT-qPCR detection of the expression levels of Ccl3, Ccl4, Ccl5 and Ccr5 in whole muscle in MVC vs. DMSO group, n=5. U Bulk RNA-seq was performed in freshly isolated MuSCs from DMSO or MVC-treated mice and up- or down-regulated DEGs were identified using Log2FC \u0026gt;0.5 as a cut-off. V GO analysis of the above-identified 231 down-regulated DEGs. W GSEA analysis of the repressed SASP expression in the above MVC-treated MuSCs. X RT-qPCR detection of the expression levels of Ccl3, Ccl4, Ccl5 and Ccr5 in the above MuSCs, n=5. All the bar graphs are presented as mean + SD, Student’s t-test was used to calculate the statistical significance (B, D-J, M-P, T, X): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, n.s. = no significance.\u003c/p\u003e","description":"","filename":"MainFigures5.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/97f2a01076ff0ae3e0177e3b.png"},{"id":71829218,"identity":"1c73aa67-61ed-4aa8-8b90-9c1722d4ad70","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1021550,"visible":true,"origin":"","legend":"\u003cp\u003eDefining TFs governing senescence state and SASP induction in human muscle. A Plots showing the predicted TFs governing senescence state shared by at least two cell types. B-C Box plots showing predicted ATF3 ATAC accessibility level senescent vs. non-senescent cells (B) or aged vs. young groups (C). D-E Box plots showing the ss-GSVA gene set scores of target genes activated (D) or repressed (E) by ATF3. F Network visualization of representative GO terms and pathways of ATF3- modulated DEGs in each cell type of aged vs. young muscle. The nodes represent GO terms or pathways, and the pie plots display the proportion of genes corresponding to a specific GO term or pathway in each cell type. G Network visualization of ATF3 targeted up- or down-regulated senescent genes in each cell type. Node size positively correlates with the number of cell types with its embedded pie chart indicating the number of up- and down-regulated DEGs. Each connecting line represents SnDEGs in the corresponding cell type with its color indicating log2fold change (FC) values. H-I Network visualization of core activator (H) or repressors (I) TFs in each cell type between old and young groups. Outer nodes display different cell types and the node color represents regulation score of all TF-SASP associations averaged on each cell type. Inner nodes positively correlate with the number of all TF-SASP pairs for each cell type. Each connecting line represents the number of SASP factors regulated by certain TF for each cell type. J Heatmap showing JUNB-SASP regulation score for each cell type. K Heatmaps highlighting smoothed normalized JUNB DORC accessibility, SCTnormalized RNA expression, and DORC-RNA difference for JUNB target SASP genes in MuSCs (n = 32). Student’s t-test was used to calculate the statistical significance (B-E): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, n.s. = no significance\u003c/p\u003e","description":"","filename":"MainFigures6.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/bd4c5920a25e28f78ddbfeb3.png"},{"id":71829216,"identity":"9b8606ec-9f60-4c44-8497-8a4a0aa4174e","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":168777,"visible":true,"origin":"","legend":"\u003cp\u003eJUNB activates SASP induction in senescent MuSCs via enhancer regulation. A Heatmap showing snATAC-seq detected DORC regulation scores for top-ranked TF-SASP association in human MuSCs. B Violin plot showing the snATAC-seq detected chromatin accessibility level of predicted human (h)JUNB binding sites in young vs. aged human MuSCs. C Violin plot showing the normalized expression level of hJUNB in young vs. aged human MuSCs. D MuSCs were freshly isolated from young and aged donors for RT-qPCR detection of the expression levels of hJUNB and SASP targets, n=4. E MuSCs were freshly isolated from young (2 m) and aged (24 m) mice for RTqPCR detection of the expression levels of mouse (m)JunB and SASP targets, n=3. F MuSCs were freshly isolated from Ctrl or JunB-iKO mice for RT-qPCR detection of the expression levels of mJunB SASP targets, n=5. G MuSCs were isolated from young mice and transfected with Ctrl or JunB overexpressing plasmid; RT-qPCR detection of the expression levels of mJunB SASP targets in the above cells, n=3. H Pie chart showing the distribution of snATAC-seq predicted hJUNB binding sites in young and aged human MuSCs. I MuSCs were freshly isolated from young (2m) and aged mice (24m) and JunB CUT\u0026amp;RUN-seq was performed; Pie chart showing the distribution of mJunB binding. J Average profile plot showing the H3K27ac signal surrounding the above detected mJunB binding sites (+/- 1000bp). K Pie chart showing the overlapping of mJunB potential target genes (promoter and enhancer bound) in young and aged mice MuSCs. L Pie chart showing the overlapping of the above mJunB target genes and classical SASP genes. The young and aged unique SASP targets are listed. M Genomic snapshots on Cxcl1 locus showing the binding peaks of mJunB and H3K27ac in young and aged MuSCs. N-O Genomic coverage plot on CXCL1 locus showing the predicted hJUNB binding peaks in Sn vs. nSn (N) and young vs. aged (O) human MuSCs. P Chromatin openness level (DORC) versus normalized gene expression (SCT) dynamics of CXCL1 gene along MuSC aging pseudotime. Dotted line represents LOESS fit to the values obtained from sliding window bin averaged from DORC accessibility or SCT expression levels (n = 100 cells per bin). All the bar graphs are presented as mean + SD, Student’s t-test was used to calculate the statistical significance (B-G): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, n.s. = no significance.\u003c/p\u003e","description":"","filename":"MainFigures7.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/8add6e5761181783299da5f0.png"},{"id":71829217,"identity":"c12aa0c3-5de5-42b4-ba6c-8a47a1459870","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":434893,"visible":true,"origin":"","legend":"\u003cp\u003eJUNB inhibition rejuvenates senescent human fibroblasts. A Top: Schematic of the experimental design for inducing senescence in IMR-90 human fibroblast by treating cells with Etoposide (ETO) or passaging for 10 (P10) generations. Bottom: SA-β-GAL staining showing the senescent IMR-90 cells ETO treatment or P10. Right: Quantification of the SA-β-GAL+ cells. Scale bar: 50 μm, n=5. B RT-qPCR detection of the expression levels of senescent marker genes (P14, P16, P19, P21) in the above-treated cells, n=3. C RT-qPCR detection of the expression levels of JUNB target genes in the above-treated cells, n=3. D Left: Schematic of the experimental design for testing the effect of JUNB knockdown by siRNA oligos on ETO-induced senescent IMR-90 cells. Right: RTqPCR confirmation of the JUNB knockdown in the above cells, n=3. E SA-β-GAL staining showing the percentage of senescent cells after the JUNB knockdown. Scale bar: 50 μm, n=5. F RT-qPCR detection of the expression levels of senescent marker genes in the above cells, n=3. G RT-qPCR detection of the expression level of CXCL1 in the above cells, n=3. H Left: Schematic of the experimental design for testing the effect of JUNB knockdown by siRNA oligos in P10 senescent IMR-90. Right: RT-qPCR confirmation of the expression level of JUNB in the above-treated cells, n=3.I SA-β-GAL staining showing the percentage of senescent cells after the JUNB knockdown. Scale bar: 50 μm, n=5. J RT-qPCR detection of the expression levels of senescent marker genes in the above cells, n=3. K RT-qPCR detection of the expression level of CXCL1 in the above cells, n=3. L Left: Schematic of the experimental design for testing the effect of JUNB inhibition by T5224 treatment in P10 senescent IMR-90 cells. Right: RT-qPCR detection of the expression level JUNB in the abovetreated cells, n=3. M SA-β-GAL staining showing the percentage of senescent cells in the abovetreated cells. Scale bar: 50 μm, n=5. N RT-qPCR detection of the expression levels of senescent marker genes in the above cells, n=3. O RT-qPCR detection of the expression level of CXCL1 in the above cells, n=3. P Left: Schematic of the experimental design for testing the effect of JUNB inhibition by T5224 treatment in P10 senescent IMR-90 cells. Right: RT-qPCR detection of the expression level of JUNB in the above cells, n=3. Q SA-β-GAL staining showing the percentage of senescent cells in the above cells. Scale bar: 50 μm, n=5. R RT-qPCR detection of the expression levels of senescent marker genes in the above cells, n=3. S RT-qPCR detection of the expression level of CXCL1 in the above cells, n=3. T Schematic of the experimental design for conducting JUNB CUT\u0026amp;RUN-seq in Ctrl and ETO-treated senescent IMR-90. U Pie chart showing the distribution of the identified JUNB binding sites in the above cells. V Pie chart showing the overlapping of the JUNB binding with H3K27Ac in the above cells. W Pie chart showing the overlapping of JUNB target genes in Ctrl and ETO cells. X Pie chart showing the overlapping of the identified JUNB SASP targets in Ctrl and ETO cells. Y Pie chart showing the overlapping of JUNB SASP targets regulated via E-P looping in Ctrl and ETO cells. Z Genomic snapshots on CXCL1 locus showing JUNB mediated E-P looping in Ctrl and ETO cells. A new E-P loop was gained in ETO cells. All the bar graphs are presented as mean + SD, Student’s t-test was used to calculate the statistical significance (A-S): *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, n.s.=no significance.\u0026nbsp;\u003c/p\u003e","description":"","filename":"MainFigures8.png","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/8d06d0f77cf4c4cf695d57d0.png"},{"id":86090343,"identity":"04c484f7-4eee-4027-b809-5083b3a0a8c2","added_by":"auto","created_at":"2025-07-06 07:05:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3100411,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1_covered_c8556f3c-e5f1-4958-b7cd-818430f633c8.pdf"},{"id":71829937,"identity":"3078d355-6a26-4acd-814b-c0f620b53afe","added_by":"auto","created_at":"2024-12-19 02:24:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2156094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplFigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/5c9d637ce2facb09c7c7561f.pdf"},{"id":71829213,"identity":"a2f2cb61-eb90-4f41-9f07-1e0bf55d189e","added_by":"auto","created_at":"2024-12-19 02:16:53","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":221737,"visible":true,"origin":"","legend":"","description":"","filename":"SupplInfo.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5399514/v1/561ca3492a79d2f4d09fb27b.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Multiomics mapping and characterization of cellular senescence in aging human skeletal muscle uncovers a novel senotherapeutic for sarcopenia","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"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":"Senescence, skeletal muscle, aging, MuSC, SASP, senotherapeutics, Maraviroc, JunB","lastPublishedDoi":"10.21203/rs.3.rs-5399514/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5399514/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Cellular senescence is recognized as a hallmark of organismal aging but how it drives aging particularly in human tissues is not fully understood, partly due to the complex heterogeneous nature of senescence. Here in this study, we leverage single-nucleus multiomics to profile senescence in mononucleated cells of human skeletal muscle and provide the first senescence atlas. We demonstrate the intra- and inter-populational transcriptomic and epigenomic heterogeneity and dynamics of senescence in the cells. We also identify commonalities and variations in senescence-associated secretory phenotypes (SASPs) among the cells and elucidate the function of SASPs in mediating cellular interactions and niche deregulation. Furthermore, we identify targetable SASP factors and demonstrate the possibility of using Maraviroc as a pharmacological senotherapeutic for treating age-associated sarcopenia in muscle. Lastly, we define transcription factors that govern senescence state and SASP induction in aging muscle and elucidate the key function and the underlying mechanism of JUNB in regulating SASP activation in senescent cells. Altogether, our findings demonstrate the prevalence and function of cellular senescence in skeletal muscle and identify a novel pharmacological intervention for sarcopenia.","manuscriptTitle":"Multiomics mapping and characterization of cellular senescence in aging human skeletal muscle uncovers a novel senotherapeutic for sarcopenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-19 02:16:48","doi":"10.21203/rs.3.rs-5399514/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":"1e7f9ffa-b37b-4791-a0fe-c0af91ba4d70","owner":[],"postedDate":"December 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":40110686,"name":"Biological sciences/Cell biology/Senescence"},{"id":40110687,"name":"Biological sciences/Stem cells/Muscle stem cells"},{"id":40110688,"name":"Biological sciences/Stem cells/Ageing"},{"id":40110689,"name":"Health sciences/Health care/Therapeutics/Drug therapy/Molecularly targeted therapy"}],"tags":[],"updatedAt":"2025-07-06T07:05:32+00:00","versionOfRecord":{"articleIdentity":"rs-5399514","link":"https://doi.org/10.1038/s41467-025-61403-y","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-07-05 04:00:00","publishedOnDateReadable":"July 5th, 2025"},"versionCreatedAt":"2024-12-19 02:16:48","video":"","vorDoi":"10.1038/s41467-025-61403-y","vorDoiUrl":"https://doi.org/10.1038/s41467-025-61403-y","workflowStages":[]},"version":"v1","identity":"rs-5399514","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5399514","identity":"rs-5399514","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}