Nathalie Boulet

| Anaïs Briot

| Valentin Jargaud

David Estève

Anne Rémaury

| Chloé Belles

| Pénélope Viana

Jessica Fontaine

Lucie Murphy

Catherine Déon

Marie Guillemot

Catherine Pech

| Yaligara Veeranagouda

| Michel Didier

Pauline Decaunes

Etienne Mouisel

Christian Carpéné

Jason S Iacovoni

Alexia Zakaroff-Girard

Jean-Louis Grolleau

Jean Galitzky

Séverine Ledoux

Jean-Claude Guillemot

Anne Bouloumié
email: anne.bouloumie@inserm.fr

Notch activation shifts the fate decision of senescent progenitors toward myofibrogenesis in human adipose tissue

Senescence is a key event in the impairment of adipose tissue (AT) function with obesity and aging but the underlying molecular and cellular players remain to be fully defined, particularly with respect to the human AT progenitors. We have found distinct profiles of senescent progenitors based on AT location between stroma from visceral versus subcutaneous AT. In addition to flow cytometry, we characterized the location differences with transcriptomic and proteomic approaches, uncovering the genes and developmental pathways that are underlying replicative senescence. We identified key components to include INBHA as well as SFRP4 and GREM1, antagonists for the WNT and BMP pathways, in the senescence-associated secretory phenotype and NOTCH3 in the senescence-associated intrinsic phenotype. Notch activation in AT progenitors inhibits adipogenesis and promotes myofibrogenesis independently of TGFβ. In addition, we demonstrate that NOTCH3 is enriched in the premyofibroblast progenitor subset, which preferentially accumulates in the visceral AT of patients with an early obesity trajectory. Herein, we reveal that NOTCH3 plays a role in the balance of progenitor fate determination preferring myofibrogenesis at the expense of adipogenesis. Progenitor NOTCH3 may constitute a tool to monitor replicative senescence and to limit AT dysfunction in obesity and aging.

| INTRODUC TI ON

Central obesity and aging share similarities in terms of their metabolic and inflammatory alterations, such as the accumulation of visceral fat depots, insulin resistance, chronic low-grade inflammatory state [START_REF] Trim Trim | Parallels in Immunometabolic adipose tissue dysfunction with ageing and obesity[END_REF], and elevated risk to develop severe chronic pathologies, including type 2 diabetes and cardiovascular diseases.

The fact that obesity shares features with aging led to the concept that excessive fat mass accelerates the onset of aging-related disorders [START_REF] Burton | Obesity and type-2 diabetes as inducers of premature cellular senescence and ageing[END_REF]. Cellular senescence, known to be involved in both aging and age-related disorders (van Deursen, 2014), has recently also been found to play a role in obesity-associated pathologies [START_REF] Palmer | Cellular senescence: at the nexus between ageing and diabetes[END_REF]. While senescent cells can be protective against cancer development [START_REF] Campisi | Aging, cellular senescence, and cancer[END_REF], their accumulation in metabolically active organs, such as the liver [START_REF] Ogrodnik | Cellular senescence drives age-dependent hepatic steatosis[END_REF] and adipose tissue (AT; [START_REF] Minamino | A crucial role for adipose tissue p53 in the regulation of insulin resistance[END_REF], shows negative effects with aging and obesity. Cell cycle arrest triggered by external or internal stresses including telomere shortening [START_REF] Shay | Role of telomeres and telomerase in aging and cancer[END_REF], DNA damage, oxidative stress, and the excess of metabolic substrates including ATP [START_REF] Pini | Adipose tissue senescence is mediated by increased ATP content after a short-term high-fat diet exposure[END_REF] through the activation of p16Ink4a-and p53-dependent pathways, together with the senescence-associated beta-galactosidase (SAβ-gal) activity, are hallmarks of AT senescent stroma-vascular cells. In addition, mature adipocytes also express a form of cell cycle-independent senescence [START_REF] Ishaq | Palmitate induces DNA damage and senescence in human adipocytes in vitro that can be alleviated by oleic acid but not inorganic nitrate[END_REF]. The causal role of senescence on impaired energy homeostasis is demonstrated by targeting senescent cells with drug-inducible "suicide" genes driven by the p16(Ink4a; [START_REF] Palmer | Targeting senescent cells alleviates obesityinduced metabolic dysfunction[END_REF] or p21 [START_REF] Wang | Targeting p21(Cip1) highly expressing cells in adipose tissue alleviates insulin resistance in obesity[END_REF] promoter or by senolytic drugs in obese and aged mice, strategies associated with reduction of age-and obesity-related metabolic abnormalities. Many of the detrimental effects of senescence are thought to be mediated by the senescence-associated secretory phenotype (SASP) that affects the healthy neighbor cells by promoting low-grade inflammation and fibrosis. SASP can spread senescence itself, leading to marked alterations in tissue homeostasis and function and thereby lead to systemic insulin resistance (Xu, Tchkonia, et al., 2015). Whether cellintrinsic mechanisms are also involved in this process remains to be established.

Progenitors, identified as CD45 -/CD34 + /CD31 -stromal cells, are major contributors in the maintenance of AT homeostasis through the renewal of dysfunctional hypertrophic adipocytes and extracellular matrix. Progenitor cells are also important in the regulation of AT growth by providing additional adipocytes leading to AT hyperplasia. Progenitors constitute a heterogeneous mesenchymal stromal cell population of specialized subsets as shown by single-cell RNA sequencing approaches [START_REF] Emont | A single-cell atlas of human and mouse white adipose tissue[END_REF]. Using single-cell flow cytometry approaches, we previously identified tissue nonspecific alkaline phosphatase (ALPL or MSCA1) and NGFR (or CD271) as respective markers of the preadipocyte and the premyofibroblast in human fat depots [START_REF] Esteve | Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells[END_REF]. Impaired adipogenesis has been associated with senescence in aged/obese mice and in human AT stromal cells (Le [START_REF] Pelletier | Metformin alleviates stress-induced cellular senescence of aging human adipose stromal cells and the ensuing adipocyte dysfunction[END_REF][START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF]. Several data are in line with an environmental impact of the SASP-derived factors including antiadipogenic Activin A [START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF] and pro-fibrotic Osteopontin [START_REF] Sawaki | Visceral adipose tissue drives cardiac aging through modulation of fibroblast senescence by Osteopontin production[END_REF]. But integration of senescent environmental cues, together with progenitor intrinsic mechanisms controlling their fate, have yet to be defined. In addition, a better understanding of the molecular basis of progenitor aging is of interest to monitor and target senescence of mesenchymal stromal cells for future cell-based therapy in regenerative medicine.

The anatomical repartition of fat depots and the maintenance of AT expandability are major determinants of human metabolic health. Accumulation of visceral AT (VsAT), as observed in central obesity and with aging, is deleterious and associated with increased risk to develop cardiometabolic pathologies. In the present study, we performed flow cytometry analyses to investigate the stromal senescent state according to fat depot location using a human cohort of obese subjects and unbiased large-scale transcriptomic and proteomic approaches on human immuno-selected CD45 -/CD34 + / CD31 -AT progenitors. Our observations show that TGFbeta/BMP, WNT, and NOTCH developmental pathways are dysregulated in these senescent progenitors. GREM1 and SFRP4, endogenous antagonists to the BMP and WNT pathways, and INHBA were found to be preferentially upregulated in SASP from VsAT. Cells forced into replicative senescence upregulated intrinsic NOTCH3 receptor expression. Modulation of NOTCH activity by immobilized ligand and by gamma-secretase inhibitor demonstrates that Notch signaling is central in the pro-myofibrogenic/antiadipogenic fate triggered by replicative senescence. The link between NOTCH3 and myofibrogenesis is further supported by gene expression studies on both human and mouse AT and analyses of human progenitor subsets.

| ME THODS

| Human adipose tissues

Subcutaneous human AT was obtained from healthy adult women undergoing dermolipectomy (mean body mass index 27.5 kg/ m 2 ± SD 3.324, mean age 41.9 years ± SD 9.8). The protocol was approved by Ministère de la Recherche (DC2008-452). Paired subcutaneous abdominal and visceral (omental) AT was obtained from patients, candidates for bariatric surgery through a clinical study approved by the Institutional Review Boards registered at Clini calTr ials.gov (SENAPID NCT01525472). All donors gave their informed consent.

| Cell isolation and culture

AT was digested with dispase (2.4 U/ml in PBS, pH 7.4, volume/ volume, Gibco) and then type I collagenase (250 U/ml in PBS, 2% BSA, pH 7.4, volume/volume, Sigma-Aldrich) for 30 min at 37°C for the dermolipectomy, or with collagenase only for the SENADIP AT.

Cell suspensions were filtered through a 250 μm filter. The stromavascular cells (SVC) were obtained after centrifugation and treatment with erythrocyte lysis buffer (155 mmol/L NH 4 Cl; 5.7 mmol/L K 2 HPO 4 ; 0.1 mmol/L EDTA; pH 7.3) for 10 min. Finally, matrix fragments were removed using successive filtrations through 100, 70, and 40 μm nylon meshes. The viable recovered cells were counted and further analyzed by flow cytometry or used to isolate the cell subsets by either magnetic beads-based selection or cell sorter.

The CD45 -/CD34 + /CD31 -progenitor cells were obtained from SVC by elimination of the immune and endothelial cells using CD45 + depletion kit (Stemcell Technologies) followed by CD31 + depletion (R&D Systems or Dynal, Thermofisher), followed by CD34 + selection kit (Stemcell Technologies) according to the manufacturer's instructions. Purity of the progenitor cells was assessed by flow cytometry.

Cells were cultured at 37°C under 21% O 2 and 5% CO 2 . For adipogenic differentiation, progenitor cells were seeded at high density (120,000 cells/cm 2 ) in ECGM-MV (Promocell) with 50 mg/ ml penicillin-streptomycin for 48 h, trypsinated, and seeded in culture plates containing basal defined adipogenic medium (ECBM (Promocell) with 66 nmol/L insulin, 1 nmol/L triiodothyronine, 0.1 μg/ ml transferrin, 100 nmol/L cortisol) supplemented with 3 μmol/L rosiglitazone and isobuthylmethylxantine (IBMX, 0.25 mmol/L) and precoated with human recombinant NOTCH ligands: IgG1-Fc, JAG1-Fc and DLL4-F (Invitrogen) diluted in PBS and coated at 2 μg/ cm 2 overnight at 4°C or 3 h at room temperature (RT). After 3 days, the medium was replaced by basal defined adipogenic medium for the following 7 days. At day 10, cells were either fixed in 4% PFA solution at RT for 10 min or lysed for RNA extraction. For myofibrogenic differentiation, progenitor cells were seeded at high density (120,000 cells/cm 2 ) in ECGM-MV for 48 h, trypsinated, and seeded on coated recombinant NOTCH ligands in ECBM 1% fetal calf serum (FCS), supplemented or not with recombinant TGFβ1 (5 ng/ml, Peprotech), and treated or not with γ-secretase inhibitor LY411575 (10 μmol/L, Sigma-Aldrich) or TGFβ1 receptor inhibitor SB431542 (10 μmol/L, Sigma-Aldrich) for 4 days. At day 4, cells were either fixed with 4% PFA or lysed for RNA extraction. For serial passaging, progenitor cells were seeded at low density (5000 cells/cm 2 ) in ECGM-MV, and then at 80% confluency, cells were trypsinated and seeded at low density for next passage, or at high density on coated ligand in ECBM 1% FCS. Immuno-selected P1 progenitor cells were treated with hydrogen peroxide (H 2 O 2 ) 0.1 μmol/L during 24 h, then lysed for RNA extraction or by doxorubicin (0.2 μM, Sigma-Aldrich) or etoposide (1 μM, Sigma-Aldrich) for 72 h, then either lysed for RNA extraction, or fixed with 4% PFA. For senolytic treatment, P3 and P6 progenitor cells were seeded at high density on IGG or DLL4 in ECGM-MV and treated with dasatinib (50 nM, Sigma-Aldrich) and quercetin (20 μM, Sigma-Aldrich) for 4 days then lysed for RNA extraction. For conditioned media analyses, progenitor cells (native or passaged) were seeded at high density (120,000 cells/cm 2 ) in ECGM-MV for 24 h, followed by three washes with ECBM and incubated for 24 h within ECBM. Media were then collected and frozen at -80°C before mass spectrometry analyses. The progenitor cell subsets, that is, MSCA1 + , -/CD271 + (MSCA1 -/CD271 + ), and -/-(MSCA1 -/CD271 -) were isolated using a cell-sorting approach as described previously [START_REF] Esteve | Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells[END_REF] and lysed for RNA extraction or cultured under myofibrogenic condition.

| Senescence-associated β -galactosidase colorimetric staining

After fixation with 0.5% glutaraldehyde (5 min for cells and 10 min for tissue), tissue pieces or cells were incubated for the next 16 h with 4 mM K3Fe(CN) 6 , 4 mM K4Fe(CN) 6 , 2 mM MgCl2, and 400 μg/ ml X-Gal in C 3 H 7 NO (dimethylformamide) in PBS/MgCl2 pH 6.0 and after washes, examined by microscopy (microscope Nikon Eclipse TE300).

| Senescence-associated β -galactosidase fluorescence staining and flow cytometry approaches

100,000 SVC were incubated with fluorescent-labeled antibodies (V500-CD45, PerCP-CD34, and V450-CD31 (BD Biosciences), PE-MSCA1, APC-CD271, and PE-Vio770-CD14 (Miltenyi Biotec)) or appropriate isotype control for 30 min at 4°C in PBS 0.5% BSA and 2 mmol/L EDTA. Cells were washed with PBS and analyzed using a FACS Canto™ II flow cytometer. Beta-galactosidase activity was performed using ImaGene Green C 12 FDG lacZ Gene Expression Kit (Molecular Probes). 250,000 cells in ECBM 0.1% BSA without phenol red, pretreated with chloroquine (30 μmol/L) for 1 h at 37°C under 5% CO 2 , were further incubated for the next 3 h with 33 μmol/L FITC C 12 FDG. After washing steps, antibodies or appropriate isotype control were added (PerCP-CD34, PE-Vio770-CD14, V450-CD31, and BV510-CD45) for 20 min at 4°C. Cells were washed with PBS and analyzed using a FACS Canto™ II flow cytometer. Analyses were performed with Diva Pro software (BD Biosciences) or FlowJo (BD Biosciences). Scratch wound was performed according to the manufacturer's instructions using the 96-well WoundMaker (Incucyte, Sartorius). After PBS washes, media were changed to ECBM 1% FCS in the presence or not of LY411575 (10 μmol/L), or in the presence of TGFβ1 (5 ng/ml), or SB431542 (10 μmol/L) and recorded every 3 h using the Incucyte SX5 during 72 h. Wound closure was analyzed using the Incucyte Scratch Wound Analysis Software Module (Sartorius, France).

| Scratch wound assay

| Isolation of SVC from mouse AT

Four-month-old male C3H/HeOuJ mice (Charles River Laboratories France) were fed a 45% high-fat diet (45% energy as fat, Research Diets D12451) up to 6 weeks. Mice were housed in accordance with French and European Animal Care Facility guidelines at 21 °C with food and water provided ad libitum, and maintained on a 12-h light, 12-h dark cycle. Mice were euthanized after an overnight fasting.

Perigonadal AT was excised and directly digested as described previously [START_REF] Vila | Immune cell toll-like receptor 4 mediates the development of obesity-and endotoxemiaassociated adipose tissue fibrosis[END_REF]. SVC were lysed in QIAzol (Qiagen) for RNA extraction.

| Immunofluorescence staining

Fixed cells were blocked and permeabilized in PBS 0.1% Triton X-100 and 5% serum for 30 min at RT and then incubated overnight at 4°C with primary antibodies (mouse anti-αSMA, Dako 1A4, 1:100; rabbit anti-NOTCH3, Abcam ab23426, 1:200, mouse anti-γH2AX, EMD Millipore JBW301, 1:200). After washing steps, cells were incubated for 1 h at RT with appropriate Alexa Fluor-conjugated secondary antibodies (Invitrogen). Nuclei were stained with DAPI (0.5 μg/ml, Invitrogen), and lipid accumulation was visualized with BODIPY 493/503 staining (10 μg/ml, Invitrogen) for 15 min at RT. Images were taken with a fluorescent (Nikon Eclipse TE300, software NIS-Elements 2.5 BR, Nikon®) or confocal microscope (ZEISS LSM780, ZEN software). Image analysis was performed with ImageJ software.

Nuclei were counted from the DAPI staining, and the results were the mean of 5 images for each sample.

| Western blot analysis

Cells were lysed with RIPA buffer supplemented with antiproteases, and 2.5 μg of protein extract quantified by DC protein assay (Bio-Rad) was used for the western approach. Primary antibodies rabbit anti-NOTCH3 (Abcam ab23426, 1:1000), mouse antiβ-tubulin (Cell Signaling D3U1W, 1:1000, as loading control) were incubated overnight at 4°C in TBS buffer with 5% BSA or 5% milk. Detection was performed with an appropriate HRP-coupled secondary antibody (Cell Signaling Technology) incubated for 1 h at RT and ECL reagent (Amersham). Densitometry was quantified using Chemidoc detection system (Bio-Rad laboratories).

| Transcriptional analysis

Total RNA was isolated from human cells using Quick-RNA Microprep kit (Zymo Research) or from murine SVC using Direct-zol RNA Miniprep Plus kit (Zymo Research) according to the manufacturer's instructions. cDNA synthesis was performed on 100-200 ng of total RNAs with Superscript III (Thermofisher) and random hexamer primers. Relative gene expression levels were assessed using Taqman® Probes and TaqMan Fast Advanced Applied mastermix (Thermofisher) on a QuantStudio™ 5 (QS5; Thermofisher). Human and murine Assay-On-Demand are listed in Table S1. Each of the samples was run in duplicate, and the relative amount was normalized to 18 S or PPIB housekeeping gene. Data were analyzed using QuantStudio Real-Time PCR software (Thermofisher).

| Label-free quantitative mass spectrometry

Adsorption of proteins on the surface of Nanozeolite LTL (NanoScape AG, Germany) was carried out for 90 min at 4°C by incubation of 0.1 mg protein/ml conditioned media and 0.1 mg/ml nanoparticles in 50 mmol/L ammonium bicarbonate buffer, pH 8.0 (ABF). After centrifugation at 16,000 g for 20 min and washes in ABF, captured proteins were suspended in 100 μl of ABF containing 0.05% AALS (Anionic Acid Labile Surfactants from Protea Biosciences). After reduction (10 mM DTT at 56°C for 30 min) and alkylation (20 mmol/L iodoacetamide for 30 min at RT in dark), bound proteins were digested with LysC (0.5 μg) for 4 h at 37°c followed by trypsin (1 μg) for 18 h at 37°C. After centrifugation, protein digests are collected and AALS hydrolyzed with 1% TFA at 37°C for 45 min. For LC-MSMS analysis of the native Sc and Vs progenitor cell secretome, Ultimate 3500 RSLC dual system (Thermo Scientific) coupled to hybrid LTQ Orbitrap Elite mass spectrometer (Thermo Scientific) equipped with a nanoelectrospray source was used. Tryptic digests were loaded onto a C18 trap column (Thermo Scientific) and washed with 0.2% HCOOH at 5 μl/min for 10 min. Peptides were eluted on a C18 reverse-phase column (Thermo Scientific) with a linear gradient of 4%-30% solvent B (H 2 O/CH 3 CN/HCOOH, 10/90/0.2 volumes) for 120 min, 30%-90% solvent B for 20 min, and 90% solvent B for 5 min, at a flow rate of 250 nl/min. The mass spectrometer was operated in the data-dependent mode to automatically switch between MS and MS/MS acquisition. Survey full-scan MS spectra (m/z 310-1600) were acquired in the Orbitrap with a resolution of 120,000 at m/z 400. For serial passaging secretome, the nanoAcquity UPLC (Waters) coupled to a Q Exactive Plus mass spectrometer (Thermo Scientific) equipped with a nanoelectrospray source was used.

Protein digests were loaded onto a nanoAcquity UPLC Trap column (Waters) and washed with 0.2% formic acid at 20 μl/min for 3 min.

Peptides were then eluted on a C 18 reverse-phase nanoAcquity column (Waters) with a linear gradient of 8-31% solvent B (H 2 O/ CH 3 CN/HCOOH, 10/90/0.2, by vol.) for 120 min, 31-91% solvent B for 20 min, and 91% solvent B for 5 min, at a flow rate of 250 nl/min.

The mass spectrometer was operated in the data-dependent mode XTandem parallel Database Search. Peptide identifications were accepted if they could be established at greater than 7.0% probability to achieve an FDR less than 1.0% by the Scaffold Local FDR algorithm. Protein identifications were accepted if they could be established at greater than 97.0% probability to achieve an FDR less than 1.0% and contained at least 2 identified peptides. Quantitative differential analysis of proteins was realized using a label-free analysis with an in-house DIFFTAL (DIFferential Fourier Transform Analysis) software algorithm as described previously [START_REF] Autelitano | Identification of novel tumor-associated cell surface sialoglycoproteins in human glioblastoma tumors using quantitative proteomics[END_REF].

| Ampliseq RNA sequencing

RNA was isolated using RNeasy Protect Mini kit (Qiagen) and suspended in RNAprotect cell reagent. RNA quality was assessed with Agilent RNA 6000 Pico Kit (Agilent) and quantified using Qubit™ RNA HS Assay Kit (Invitrogen) and Qubit 2 Fluorometer (Invitrogen). 10 ng of RNA was used for AmpliSeq transcriptome library construction. For AmpliSeq transcriptome sequencing library construction AmpliSeq™ Library PLUS, AmpliSeq Transcriptome Human Gene Expression Panel and AmpliSeq CD indexes SetA kits were purchased from Illumina and sequencing libraries were constructed as described in AmpliSeq for Illumina Transcriptome Human Gene Expression Panel reference guide (Illumina). Sequencing libraries were quantified using Qubit dsDNA HS Assay Kit and Fluorometer (Invitrogen) and converted to molar concentration using 285-bp peak. Equimolar concentrations of libraries were pooled at 4 nmol/L and used for sequencing. Pooled library was denatured and diluted as described in Denature and Dilute Libraries Guide (Illumina) and adjusted to final concentration of 1.4 pmol/L. Resulting library was sequenced on NextSeq 500 using NextSeq 500/550 High Output v2 kit with 2 × 151 bp cycle. Generated raw files were converted to FASTQ files and used for data analysis. AmpliSeq transcriptome FASTQ files were analyzed on Array studio V10.0 (Omicsoft, Qiagen). Following raw read QC, first and last 10 bases were trimmed and mapped to reference genome Human B38. The read count data were generated using GeneModel RefGene20170606.

Resulting data were normalized by DESeq package, transformed to log2 value, and used for statistical analysis using NetworkAnalyst [START_REF] Zhou | NetworkAnalyst 3.0: A visual analytics platform for comprehensive gene expression profiling and meta-analysis[END_REF].

| Statistical analyses

Statistical analyses were performed using Prism (GraphPad Software). Comparisons between 2 groups were analyzed either paired or unpaired analysis and two-tailed Student's t test or Wilcoxon test depending on data distribution. Comparison between more than 2 groups was analyzed by either one-way ANOVA or two-way ANOVA or nonparametric Kruskal-Wallis test, followed by Dunn's, Dunnet's, Tukey's, or Sidak's multiple comparison test for (n) independent experiments. Differences were considered statistically significant when p < 0.05. the total SAβ-gal+ stromal cells, VsAT had higher percentage of progenitors and lower of macrophages than ScAT (Figure 1c). Per tissue mass, VsAT contained a higher number of SAβ-gal+ senescent progenitors when compared to ScAT, with no corresponding difference in the number of senescent macrophages (Figure 1D).

| RE SULTS

| Fat depot location from obese patients impacts senescence of progenitors

ITLN1 PLAT CXCL6 KRT85 LIF INHBA LBP GREM1 CHI3L1 PTGDS MSLN CYR61 CFI F2 PLAU NRP2 SERPINC1 IL6 IGHG1 SFRP4 SLPI C7 LOX ADAMTS1 APOA1 IGHG4 GC PLG GALNT2 HPX MMP9 PLXDC2 CMA1 TF F5 AGRN LTBP4 TGFBI C1QBP IGFBP3 COL18A1 ARPC1A IGHG3 CHID1 ITIH4 CXCL1 C4B SERPINE1 IL8 CXCL3 IGFBP4 SERPINB2 OGN IGFBP7 SPON1 PAPPA IGF2 SERPINE2 CCDC80 THBS1 APLP2 C4A/C4B EMILIN2 SFRP2 FGF7 COL12A1 COL3A1 TNXB COL6A3 CFD ECM1 CAB39L SERPINF1 FST ENPP2 CFH GSN ITGBL1 TYMP TPSAB1/TPSB2 WISP2 SOD3 CLEC3B POSTN MMP3
In the progenitor cluster, back-gating on the fat depot origin re- DEPs with the freely available secretome database, the SASP atlas [START_REF] Basisty | A proteomic atlas of senescence-associated secretomes for aging biomarker development[END_REF], the SenMayo geneset [START_REF] Saul | A new gene set identifies senescent cells and predicts senescenceassociated pathways across tissues[END_REF] and factors identified in human AT senescent progenitors [START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF]Xu, Tchkonia, et al., 2015) A marked increase in the number of SAβ-gal+ progenitor cells was observed as early as P3 in both nonconfluent and confluent cells (Figure 2a). In addition, increases in cell size and doubling time and in the expression levels of CDKN2A (p16) and CCND1 (Cyclin D1) were observed while CDKN1A levels (p21) were not altered (Figure 2b). P6 progenitors although both doxorubicin and etoposide increased the expression of senescent markers including CDKN1A and CCND1 and γH2AX nuclear foci (Figure 3a and Figure S2). Interestingly, the effect of replicative senescence was specific for NOTCH3, as NOTCH1 remained unchanged (Figure 3a). The increased level of NOTCH3 mRNA with replicative senescence was associated with an increased level of the cleaved form of NOTCH3 protein with the apparent molecular weight of 100 kDa (Figure 3b). The basal levels of the canonical Notch target genes HEYL and HES1 were not changed with replicative senescence (Figure 3c). fect was not related to a pro-senescent impact of Notch activation since it did not increase but even rather slightly decreased the expression of both CDKN2A and CCND1 at P3 and CCND1 at P6 without affecting the expression level of CDKN1A (Figure 3g).

vealed

Paired analysis of the

| NOTCH activation shifts progenitor cell fate balance toward myofibrogenesis over adipogenesis

To investigate the impact of Notch signaling on progenitor differentiation, immuno-selected progenitor cells (P1) were seeded on immobilized NOTCH ligands JAG1 (a member of the Jagged family)

or DLL4 and maintained under adipogenic or myofibrogenic culture conditions.

Under adipogenic conditions (Figure 4a), DLL4 and JAG1 ligands had different effects on NOTCH3 activation. Stimulation with DLL4, and not with JAG1, led to a rapid and transient increase in the Notch target gene HES1 at day 1. By contrast, DLL4 led to a marked induction of NOTCH3 mRNA at day 1, which remained elevated until day 10, while the expression of NOTCH1 was weakly increased only at day 1 (Figure 4b). Notch activation by DLL4 led to a mild, albeit significant, decrease in adipogenesis, as shown by the decrease in lipidladen cells (stained with Bodipy), without changing the number of cells (Figure 4c,d). It also reduced the expression of adipogenic genes (ADIPOQ, GPDH, and PPARG2) and brite adipogenic genes (UCP1 and ELOVL3; Figure 4e). Adipogenic differentiation per se decreased the expression of NOTCH3 and tended to increase the one of NOTCH1

(Figure 4b). Likewise, isolated mature adipocytes expressed lower levels of NOTCH3 and higher levels of NOTCH1 compared with progenitor cells (Figure S3). Under myofibrogenic culture conditions in the presence of TGFβ (Figure 4f), DLL4 but not JAG1 induced an increase of HES1 and NOTCH3 mRNA levels, which remained elevated until day 4 (Figure 4g). NOTCH1 expression was not significantly modulated under the same conditions (Figure 4g). Notch

| Native premyofibroblasts accumulate in human VsAT with high levels of senescence and are the target of the NOTCH pathway

Obese patients were grouped in tertiles of low, intermediate, and

high VsAT progenitor senescence. The group of patients with the highest percentage of SAβ-gal+ progenitors in VsAT had also a higher percentage of SAβ-gal+ progenitors in ScAT (Figure 6a).

Among the clinical and anthropometrical characteristics and in agreement with the multivariate analysis (Figure 1e), the history of obesity reflected by the patient's BMI at the age of 20 was determinant of the degree of senescence in VsAT (Table 2). Age was also statistically significant between low and high senescence groups but with younger AT donors in the high senescence group (Table 2).

Considering the two groups of patients with low and high percentage of VsAT senescent progenitors, we analyzed the progenitor subsets: MSCA1-/CD271-(-/-) progenitors, MSCA1 -/CD271+ (-/ CD271 + ) premyofibroblasts, and MSCA1 + preadipocytes by flow cytometry. While the number of progenitor subsets was not different in ScAT between the two groups, there was a marked accumulation of -/CD271 + premyofibroblasts in VsAT from the high senescence group (Figure 6b). The adipocyte diameter distribution exhibited no differences in ScAT regardless of the degree of senescence; however, we found a reduction in the percentage of 20 μm small adipocytes in VsAT from the high senescence group (Figure S6). Finally, the three progenitor subsets were immuno-selected from ScAT. RTqPCR analyses revealed higher expression levels of both NOTCH3 and the NOTCH target gene HEYL in the -/CD271 + subset compared with -/-and MSCA1 + progenitor subsets (Figure 6c). Immuno-selected -/CD271 + premyofibroblasts and -/-progenitors were seeded on DLL4 under basal conditions for 4 days (Figure 6e).

| DISCUSS ION

There has been an increasing amount of evidence, implicating that adipose tissue (AT) senescence plays a role in both obesity-and ageinduced processes responsible for metabolic abnormalities. We show that SAβ-Gal-positive cells accumulate in both ScAT and VsAT of obese subjects by colorimetric imaging approaches, as described previously [START_REF] Conley | Human obesity induces dysfunction and early senescence in adipose tissue-derived mesenchymal stromal/stem cells[END_REF][START_REF] Gustafson | Reduced subcutaneous adipogenesis in human hypertrophic obesity is linked to senescent precursor cells[END_REF][START_REF] Rouault | Senescence-associated beta-galactosidase in subcutaneous adipose tissue associates with altered glycaemic status and truncal fat in severe obesity[END_REF]. Differences in whole tissue SAβ-Gal staining have been reported between ScAT and VsAT of obese patients [START_REF] Rouault | Senescence-associated beta-galactosidase in subcutaneous adipose tissue associates with altered glycaemic status and truncal fat in severe obesity[END_REF]. Unsupervised analysis of flow cytometry datasets allows the identification of SAβ-Gal+ cells in the SVC, revealing that macrophages represent the largest proportion, followed by progenitors and endothelial cells. SAβ-Gal+ macrophages have been previously reported in AT, but their senescent phenotype remains debated [START_REF] Hall | (Ink4a) and senescence-associated beta-galactosidase 14749726[END_REF]. Additional experiments are needed to further characterize the SAβ-Gal+ macrophage population in human AT.

They are probably located within the SAβ-Gal+ crown-like structures we observed surrounding human adipocytes in this study, also described in mouse AT [START_REF] Rabhi | Obesity-induced senescent macrophages activate a fibrotic transcriptional program in adipocyte progenitors[END_REF]. While in ScAT, the majority of SAβ-Gal+ stromal cells are macrophages, progenitors and macrophages are equally represented in VsAT. No difference in the absolute number of SAβ-Gal+ macrophages is found between fat depots. The endothelial cell cluster, which does contain SAβ-Gal+ cells, consists of a limited number of cells, due to the small biopsy size, and was not analyzed further. Endothelial senescence has been shown to be sufficient to induce adipocyte dysfunction and metabolic disorders in a mouse model [START_REF] Barinda | Endothelial progeria induces adipose tissue senescence and impairs insulin sensitivity through senescence associated secretory phenotype[END_REF]. We previously reported higher endothelial senescence in VsAT from obese individuals compared with ScAT and with age in ScAT [START_REF] Briot | Senescence alters PPARgamma (peroxisome proliferator-activated receptor gamma)-dependent fatty acid handling in human adipose tissue microvascular endothelial cells and favors inflammation[END_REF][START_REF] Villaret | Adipose tissue endothelial cells from obese human subjects: Differences among depots in angiogenic, metabolic, and inflammatory gene expression and cellular senescence[END_REF]. Finally, SAβ-Gal+ progenitors are both modulated by AT location in terms of their proportion and number, with higher amounts found in VsAT. Progenitors are key cellular components for fat depot repair, physiological turnover, and expansion under energy excess. Although adipocyte turnover is considered to be a slow process in adults [START_REF] Spalding | Dynamics of fat cell turnover in humans[END_REF], chronic renewal pressure exerted on progenitor cells is higher in obese versus lean individuals due to the greater number of adipocytes. In the present study, multivariable unbiased analysis highlighted the association between senescence parameters and obesity, more marked in VsAT compared with ScAT. Moreover, the group of patients with the highest proportion of senescent progenitors in VsAT is characterized by an early obesity trajectory reflected by an increased BMI at the age of 20 years old. It is therefore tempting to speculate that high VsAT progenitor senescence is a consequence of the chronic replicative pressure exerted by a longer history of obesity. The proliferative rate of AT progenitor cells is distinct according to fat depot location, with less proliferation in visceral compared with subcutaneous AT [START_REF] Tchkonia | Fat depot-specific characteristics are retained in strains derived from single human preadipocytes[END_REF]. The present data suggest that the depot-specific differences in senescence may be an additional determinant of the progenitor proliferation rate. Combined transcriptomics and proteomics datasets, obtained from both native and in vitro replicative senescent immuno-selected progenitors and comparison with other available SASP datasets, highlight common core SASP factors in both ScAT and VsAT including INHBA as well as fat depotand replicative senescence-specific SASP factors. In particular, GREM1 and SFRP4, endogenous antagonists of the BMP and WNT pathways, respectively, are markers of the VsAT secretome and elevated with replicative senescence. SFRP4 and GREM1 are not only emerging adipokines with higher expression in VsAT [START_REF] Hedjazifar | The novel Adipokine gremlin 1 antagonizes insulin action and is increased in type 2 diabetes and NAFLD/NASH[END_REF] but also contained within published senescent gene sets [START_REF] Gustafson | Reduced subcutaneous adipogenesis in human hypertrophic obesity is linked to senescent precursor cells[END_REF] (https://seneq uest.net/). In addition to finding BMP and WNT antagonists in the SASP, our study highlights the importance of the Notch developmental pathway in the senescenceassociated intrinsic phenotype. Increased NOTCH3 expression has already been reported during replicative senescence induced by telomere shortening in human cell lines [START_REF] Cui | Notch3 functions as a tumor suppressor by controlling cellular senescence[END_REF]. Our present data demonstrate that NOTCH3 expression also increased with senescence in human AT progenitors. This increase is specific for were not modulated with cell passaging, suggesting that replicative senescence is not associated with a sustained activation of Notchdependent pathway without precluding a pulsatile activation [START_REF] Nandagopal | Dynamic ligand discrimination in the Notch signaling pathway[END_REF] and/or oscillatory changes in the levels of these genes with short mRNA half-lives [START_REF] Kobayashi | Expression dynamics and functions of Hes factors in development and diseases[END_REF]. Developmental pathways modulate progenitor fate during self-renewal and differentiation. While BMP and WNTdependent pathways are potent pro-adipogenic stimuli in AT, the net impact of NOTCH signaling on adipogenesis, in particular NOTCH1, is controversial [START_REF] Shan | Roles of Notch signaling in adipocyte progenitor cells and mature adipocytes[END_REF]. As an antidevelopmental process, senescence is more often associated with impaired stem cell/progenitor differentiation. Senescent AT stromal cells from aged/obese mice and humans exhibit a decreased adipogenic potential (Le [START_REF] Pelletier | Metformin alleviates stress-induced cellular senescence of aging human adipose stromal cells and the ensuing adipocyte dysfunction[END_REF][START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF], while a targeted reduction in senescence enhances adipogenesis [START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF].

Depending on tissue context and cell type, senescence may also promote the myofibrogenic differentiation, such as in wounded skin [START_REF] Demaria | An essential role for senescent cells in optimal wound healing through secretion of PDGF-AA[END_REF] or inhibit it through a modulation of Notch/ TGFβ axis [START_REF] Lopez-Antona | Dynamic regulation of myofibroblast phenotype in cellular senescence[END_REF]. Our data demonstrate that Notch activation has a major impact in the determination of AT progenitor fate since it impairs white and brite adipogenesis while promoting myofibrogenesis. Both NOTCH ligands, DLL4 and JAG1, did not trigger similar effects, with weak to no impact of JAG1.

Although additional experiments will be needed to clearly define the underlying molecular mechanism, distinct ligands can activate, through the same Notch receptor, different target genes and cell fate by defining distinct Notch receptor activation dynamics, that is, sustained or pulsatile [START_REF] Nandagopal | Dynamic ligand discrimination in the Notch signaling pathway[END_REF]. Interestingly, the dynamic fluctuation of NOTCH1 activity associated with oncogeneinduced senescence has been involved in the balance between distinct SASP promoting a TGFβ rich secretome [START_REF] Hoare | NOTCH1 mediates a switch between two distinct secretomes during senescence[END_REF]. involved in fibrosis [START_REF] Ramachandran | Resolving the fibrotic niche of human liver cirrhosis at single-cell level[END_REF]. Since positive correlations between NOTCH3 (but not with NOTCH1) and myofibrogenic-related gene expression were observed in human and mouse AT, it is strongly suggested that NOTCH3 is also the active Notch receptor in AT myofibrogenesis although gene editing approaches will permit to clearly state about the molecular identity of and sufficient to induce their differentiation. Additionally, the group of patients with the highest progenitor senescence in VsAT is characterized by higher -/CD271 + premyofibroblast accumulation, supporting the hypothesis that NOTCH activity contributes to the depot-specific enrichment of -/CD271 + subsets that we previously reported [START_REF] Esteve | Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells[END_REF]. Our findings also suggest that it will be worthwhile to investigate the role of NOTCH3 in wound healing, especially in light of a recent study describing that insufficient induction of AT senescence after injury is a pathological mechanism of diabetic wound healing [START_REF] Kita | Altered regulation of mesenchymal cell senescence in adipose tissue promotes pathological changes associated with diabetic wound healing[END_REF].

As a consequence of the defect in adipocyte renewal, the accumulation of SAβ-Gal+ cells in mouse and human ScAT has been associated with adipocyte hypertrophy [START_REF] Gustafson | Reduced subcutaneous adipogenesis in human hypertrophic obesity is linked to senescent precursor cells[END_REF][START_REF] Xu | Targeting senescent cells enhances adipogenesis and metabolic function in old age[END_REF] and has a negative impact on systemic metabolism. In agreement with a recent study [START_REF] Ishaq | Palmitate induces DNA damage and senescence in human adipocytes in vitro that can be alleviated by oleic acid but not inorganic nitrate[END_REF], we did not observe differences in adipocyte hypertrophy nor in systemic metabolic parameters in the patients grouped according to VsAT

  tissue, myofibrogenesis, NOTCH signaling, obesity, progenitors, senescence 14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 3 of 24 BOULET et al.

  p96 plate (Incucyte® Imagelock 96-well plate, Sartorius, France) was coated overnight at 4°C with IgG and DLL4. Immuno-selected progenitor cells were plated in ECGM-MV at 30-40,000 cells/well on IgG/ DLL4-coated wells in the presence or not of 10 μmol/L of LY411575 14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License or of 10 μmol/L of SB431542 or on uncoated wells, and left overnight.

14749726, 0 ,

 0 Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License to automatically switch between MS and MS/MS acquisition. Survey full-scan MS spectra (from m/z 325-1300) were acquired with a resolution of 70,000 at m/z 200. MSMS spectra were recorded in profile type with a resolution of 17′500. All samples were injected in triplicate. The LC-MS/MS data, acquired using the Xcalibur software (Thermo Fisher Scientific), were processed using a homemade Visual Basic program software developed using XRawfile libraries (Thermo Fisher Scientific) to generate an MS/MS peak list used for database searching and a file used for quantitative analysis. Database searches were performed using internal MASCOT server (Matrix Science) using the Swiss-Prot human database. Mascot results were imported into Scaffold software (version 4.4.1.1) and also used for

  Statistical analyses were realized with DanteR program, an R-based software. The peptides quantification was normalized by the median intensity value of the detected feature population over the 102 runs, which includes 34 conditions (17 patients × 2 AT depots) and over the 36 runs, which includes 12 conditions (3 patients × 4 levels of serial passaging), in triplicate injections. Only peptides detected at least 2 times (over replicates) are kept, and an average intensity value per sample is calculated for each peptide. A threshold value representing the minimum detectable signal level is used. The protein abundance is determined as the average of the top three most abundant peptides per protein.

  Figure 1a, SAβ-gal staining showed interindividual and interdepot heterogeneity, exhibiting a range of distinct qualitative profiles, from a diffuse low-level staining in ScAT biopsies to much higher staining in VsAT (left panel), with positive cells widely distributed in the stroma-vascular compartment or concentrated in crown-like structures surrounding adipocytes (right panel, top and bottom, respectively). Although some mature adipocytes exhibited light SAβ-Gal staining, more intense SAβ-Gal staining was found in stromal cells. To further identify and quantify SAβ-gal-positive stromal cells in human AT, stroma-vascular cells obtained after collagenase digestion of both ScAT and VsAT from 115 obese subjects were stained for fluorescent SAβ-gal activity in combination with cell surface markers (CD45, CD14, CD34, and CD31) and analyzed by flow cytometry. Unsupervised tSNE (t-distributed stochastic neighbor embedding) performed after downsampling and concatenation of ScAT and VsAT data from a panel of 55 donors highlighted macrophage, lymphocyte, endothelial cell and progenitor cell clusters based on cell surface marker expression (Figure S1a,b left panel). SAβ-gal+ cells were identified in macrophages, endothelial cells, and progenitor cells (Figure 1b right panel). Within

  higher SAβ-gal activity together with larger cell size in VsAT compared with. Principal component analysis using clinical and anthropometric variables in addition to ScAT and VsAT progenitor senescence variables was performed (Figure1e). Component 1 clearly separated two groups of variables. One group was constituted by the variables relative to progenitor senescence and BMI (at the age of 20, actual and maximal BMI). The other group was composed of parameters related to metabolic syndrome (MS) including age, waist-to-hip ratio (WHR), insulin resistance (HbA1c and HOMA-IR), triglycerides, and systolic blood pressure (SBP). HDL was clearly discriminated by component 2 and, as expected, was inversely correlated with the MS-related variables. Interestingly, the associations between BMI and senescent parameters were clearly more marked and statistically relevant in VsAT compared with ScAT (Figure1e). Analysis of the secretome of native immuno-selected ScAT and VsAT progenitor cells from 17 patients by large-scale mass spectrometry identified 428 secreted proteins. Paired analysis of ScAT and VsAT progenitor secretomes highlighted 161 differentially expressed proteins (DEPs) upregulated in VsAT progenitors and 65 in ScAT progenitors; the DEPs with the highest fold changes are shown in Figure 1f. Comparison of ScAT and VsAT

  DEPs between P3 and P6 secretomes with the one of nonsenescent P1 progenitor cells identified 34 proteins upregulated either in P3 or P6 secretomes (Figure2c) among the 342 identified secretory factors. In parallel, the comparative paired analysis of the RNA sequencing data of P6 and P1 progenitors highlighted 518 DEGs upregulated at P6 (Figure2d). The P6 DEGs were enriched in pathways related to tissue remodeling including epithelial-to-mesenchymal transition (EMT), TGFβ signaling, and hypoxia as well as inflammation. Interestingly, the Notch signaling including NOTCH3 was also part of the AT progenitors senescent transcriptome (Figure2e). Merging of the P6 DEGs and P3P6 DEPs with the native ScAT and VsAT progenitor-specific secretomes from obese patients (from Figure1f) highlighted a marked enrichment in senescence-related proteins in VsAT compared with ScAT secretomes (21 proteins vs. 4, respectively; Figure2f). Among the 21 VsAT SASP factors, 16 proteins were common with other SASP (Table1). The remaining 5 proteins were specific of the AT progenitor replicative SASP and enriched in complement and coagulation pathways (C7 and C4B) as well as in TGFβ/BMP and Wnt/β-catenin signaling, as GREM1 and SFRP4 are both secreted antagonists of BMP and WNT, respectively, and in adipogenesis-related pathways (SFRP4 and LIF). RTqPCR analysis further confirmed the upregulation of GREM1, SFRP4, and LIF as well as INHBA with AT progenitor replicative senescence (Figure1g).

F

  I G U R E 1 Senescence in progenitor cells defines a fat depot-specific pattern in obesity. (a) Colorimetric SAβ-gal staining on paired biopsies of subcutaneous and visceral adipose tissue (ScAT and VsAT). Representative views of whole AT pieces and light microscope images are shown. (b) Paired ScAT and VsAT stroma-vascular fraction (SVF) cells from 55 subjects were analyzed by flow cytometry. tSNE of data after downsampling and concatenation enabled the identification of clusters by cell type: purple macrophages (CD45 + /CD34 -/ CD31int/highFSC/HighSSC), red endothelial cells (CD45 -/CD34 + /CD31 + /HighFSC/HighSSC), green progenitor cells (CD45 -/CD34 + / CD31 -/HighFSC/HighSSC), and blue lymphocytes (CD45 + /CD34 -/CD31 -/lowFSC/LowSSC; left panel) and same tSNE colored by SAβ-gal fluorescence intensity (right panel). (c) Pie charts showing the percentage of cell types within the SAβ-gal-positive cells in ScAT and VsAT. (d) Supervised analysis of the SAβ-gal+ cells, histograms represent means ± sem of SAβ-gal+ cells per gram of tissue for progenitor cells (left) and macrophages (right) from ScAT (blue) and VsAT (red; n = 115 donors, two-way ANOVA, Tukey's post-test). (e) Principal component analyses performed on clinical and anthropometrical parameters of obese AT donors and ScAT (upper panel, blue) and VsAT (lower panel, red) progenitor senescence variables. (f) Immuno-selected progenitor cells from paired ScAT and VsAT biopsies of 17 obese subjects were maintained for 24 h in basal medium, and the conditioned media were harvested and analyzed by mass spectrometry. Heatmap of most relevant differentially expressed proteins from the 17 secretomes of ScAT (blue) and VsAT (red) progenitors (deep blue corresponding to the smallest value and yellow to the highest value)

  Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 13 of 24 BOULET et al.

  To investigate the potential involvement of Notch pathway in the modulation of the replicative SASP, pharmacological approaches were performed to activate or inhibit Notch signaling in nonsenescent and senescent progenitors. Activation of Notch signaling was achieved by immobilized Notch ligand DLL4 (a member of the Delta-like family) while inhibition by treatment with the γ-secretase inhibitor LY411575, which prevents Notch cleavage (Figure 3d). As expected, Notch activation efficiently increased the mRNA level of Notch target genes HEYL and HES1 as well as NOTCH3 itself at P1. The stimulatory effects were completely inhibited by the presence of LY411575. Similar effects were observed in P3 and P6 progenitors, clearly showing that the senescent state did not alter Notch responsiveness (Figure 3e).

Interestingly,

  Notch activation by DLL4 did not affect the expression of GREM1 nor the one of LIF. SFRP4 and INHBA, on the contrary, were upregulated regardless of the cellular state of senescence and in a γ-secretase-dependent manner (Figure 3f), indicating that Notch acted upstream of the SASP factors SFRP4 and INHBA. Such an ef-

  activation by DLL4 further enhanced myofibrogenesis, as shown by the increase in αSMA-positive cells and the expression of myofibroblast genes (ACTA2, COL1A1, and INHBA; Figure 4h,j) with no impact on total cell number (Figure 4I). Analyses of RNAseq data retrieved from whole ScAT and VsAT from the GTEx database (https://www. gtexp ortal.org) showed that NOTCH3 transcript levels were positively correlated with the ones of myofibrogenic-and SASP-related genes such as ACTA2, COL1A1, COL3A1, INHBA, GREM1, and SFRP4 and with TGFβ and EMT-related transcription factor SNAI2 but not SNAI1. Conversely, NOTCH3 levels were negatively correlated with the expression of the adipogenic-related markers ADIPOQ, GPDD1, PLIN1, and PPARG. Similar trends were observed for both ScAT and VsAT, but correlations were weaker in VsAT. These observations were specific for NOTCH3 as the correlation with NOTCH1 transcript levels exhibited the opposite pattern (Figure S4a,b).

F

  Replicative senescence-associated secretory phenotype of AT progenitor cells highlights components of the TGFβ/BMP and WNT developmental pathways. (a) SAβgal activity by colorimetric staining on nonconfluent or confluent progenitors at Passage 0 (P0), 3 (P3), and 6 (P6). Representative photomicrographs from n = 3 donors are shown. Scale bars: 50 μm. (b) Changes in cell size according to increasing passages. Results are expressed as fold change over P1, means ± SEM of n = 11-17 independent experiments (one-way ANOVA, Dunnett's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 compared with P1); changes in doubling time according to increasing passages. Values are means ± SEM of n = 11-17 independent experiments (one-way ANOVA, Dunnett's post-test, **p < 0.01, ***p < 0.001 compared with P2, changes in mRNA expression of CDKN2A, CDKN1A, and CCND1 at P3 and P6. Results are expressed as fold change over P1, means ± SEM of n = 15 independent experiments (one-way ANOVA, Dunn's post-test, ***p < 0.001 compared with P1). (c) Heatmap of differentially expressed proteins in paired analysis between P1 and P3 and P1 and P6 secretomes from three donors, (deep blue corresponding to the smallest value and yellow to the highest value). (d) Volcano plot of the twofold and more differentially expressed genes between P1 and P6 RNA sequencing transcriptomes performed in three donors. (e) Statistically significantly enriched pathways in the 518 DEGs upregulated in P6 transcriptome in the Human Molecular Signatures Database (MSigDB) hallmark gene sets MSigDB Hallmark (GSEA). (f) Venn diagram of DEGs upregulated in the P6 transcriptome, P3 and P6P3 secretome and ScAT (left) and VsAT (right) native progenitor-specific secretomes. (g) mRNA levels of SASP proteins GREM1, SFRP4, LIF, and INHBA determined in P1, P3, and P6 progenitor cells by RTqPCR. Results are expressed as fold change over P1, means ± SEM of n = 7 donors (*p < 0.05, **p < 0.01, ***p < 0.001 compared with P1) Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License3.5 | NOTCH activation induces myofibrogenesis without exogenous addition of TGFβ and remains active in senescent cellsTo further characterize the cell-intrinsic impact of Notch activation in myofibrogenesis, immuno-selected progenitor cells (P1) were cultured in the presence or absence of DLL4 and LY411575, without TGFβ1, during 4 days. Since JAG1 had at best a slight effect on myofibrogenesis, only the DLL4 ligand was used. Notch activation was sufficient to induce myofibroblast differentiation, as demonstrated by an increase in the number of αSMA-positive cells and the induction of myofibroblast genes (ACTA2, COL1A1, and COL3A1) by day 4 (Figure5a,b). In parallel, the expression of NGFR, a marker for the premyofibroblast subset[START_REF] Esteve | Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells[END_REF], was increased within 4 days (Figure5c). Notch-induced myofibrogenesis was completely abolished in the presence of the γ-secretase inhibitor LY411575 (Figure5a-c), indicating a requirement for NOTCH receptor cleavage. Neither DLL4 nor LY411575 affected the cell number (Figure5b). In addition, wound closure assays clearly demonstrated that the stimulation of Notch signaling by DLL4 increased the migratory capacity of progenitor cells compared with the IGG control, but to a lesser extent than TGFβ treatment (Figure5d). Notch activation increased EMT-inducing transcription factors SNAI1 and SNAI2 (Figure5e) in an LY411575 sensitive manner. Immunostainings revealed a cytoplasmic fiber localization of NOTCH3, which coincided with αSMA labeling, at day 4 only in DLL4-differentiated progenitor cells (Figure5f). Treatment with TGFβ receptor inhibitor SB431542 did not impact the DLL4-induced upregulation of myofibroblast mRNA markers nor the DLL4-mediated cell migration although it partially inhibited, as expected, the one stimulated by TGFβ (Figure5g,h).C3H/HeOuJ mice, a strain known to develop AT fibrosis in diet-induced obesity[START_REF] Vila | Immune cell toll-like receptor 4 mediates the development of obesity-and endotoxemiaassociated adipose tissue fibrosis[END_REF], were fed a highfat diet for up to 6 weeks, and the visceral AT was used in RTqPCR for myofibrogenic-related genes Acta2, Col1a1, Col3a1, and Eln. While positive correlations were observed between Notch3 expression and the panel of fibrosis markers, no correlations were found with Notch1 mRNA levels (Figure S5a,b). In addition, a weak correlation was observed between Notch3 and Cdkn2a levels but not with Cdkn1a or Ccnd1. Immuno-selected ScAT progenitor cells were submitted to serial passaging and cultured at P3 and P6 for 4 days on DLL4 under basal conditions or in the presence of LY411575. Notchinduced myofibrogenesis was maintained at P3 and P6, as shown by an increased expression in myofibroblast genes (COL1A1, COL3A1, and INHBA), EMT-inducing transcription factors SNAI1 and SNAI2and premyofibroblast marker NGFR (Figure5I). All effects of DLL4 were abrogated by the γ-secretase inhibitor LY41575. Treatments of P3 and P6 progenitors with senolytics (dasatinib and quercetin) downregulated the expression of both CDKN2A and CCND1, as expected, with a stronger impact in P3 compared with P6 progenitors in the presence or not of DLL4 (Figure5j). In parallel, senolytics repressed the basal expression of myofibrogenic-related genes including COL1A1 and COL3A1 at P3 and P6 and the ones of INHBA and ACTA2 at P6, as well as the upregulated expression of COL1A and COL3A1 promoted by Notch signaling at P3 (Figure5k).

F

  Replicative senescence upregulates the expression of Notch3 and does not alter the responses to Notch activation. (a) NOTCH3 and NOTCH1 transcript levels in progenitor cells at P1, at P6, after H 2 O 2 or etoposide (eto) or doxorubicin (dox) treatments, determined by RTqPCR and RNAseq (H 2 O 2 treatment) and normalized to respective P1 control cells (values are means ± SEM of n = 3-8 donors, two-way ANOVA, Dunnett's post-test, ****p < 0.0001). (b) NOTCH3 protein level in progenitor cells at P1, P3, and P6 determined by western blot and quantification of the ratio between the shorter and the higher cleaved form normalized to the β-tubulin level. Results are expressed as fold change over P1, means ± SEM of n = 7-8 donors (one-way ANOVA, Dunn's post-test, **p < 0.01). (c) mRNA levels of HEYL and HES1 in progenitor cells at P1, P3, and P6 determined by RTqPCR (values are means ± SEM of n = 8 distinct donors, one-way ANOVA, Dunn's post-test). (d) Immuno-selected ScAT P1, P3, or P6 progenitor cells were seeded on immobilized IGG control or NOTCH ligand DLL4 and cultured in basal medium supplemented or not with gamma-secretase inhibitor LY411575 (LY) for 4 days. mRNA levels of (e) NOTCH3 and NOTCH target genes HEYL and HES1, (f) SASP factors INHBA, SFRP4, GREM1, and LIF determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG, means ± SEM of n = 7 donors (two-way ANOVA, Tukey's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 compared with IGG, $p < 0.05, $$p < 0.01, $$$p < 0.001 compared with DLL4). (g) mRNA levels of senescence markers CDKN1A, CDKN2A, and CCND1 in P3 and P6 progenitor cells determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG P3, means ± sem of n = 3-4 donors (two-way ANOVA, Dunnett's post-test)

  NOTCH3 activation induced myofibroblast differentiation of -/CD271 + premyofibroblasts only, as shown by an increase in αSMA-positive cells and myofibroblast gene expression (COL1A1, ELN, and INHBA), together Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 17 of 24 BOULET et al. with increased expression of the EMT-inducing transcription factor SNAI1 (Figure 6d,e). No effects were observed with the -/-progenitor subset.

F

  I G U R E 4 NOTCH activation inhibits adipogenesis and promotes myofibrogenesis. (a) Immuno-selected ScAT P1 progenitor cells were seeded on immobilized IGG control (white) or NOTCH ligands JAG1 (cyan) or DLL4 (pink) and cultured in adipogenic medium for 10 days. (b) mRNA levels of HES1, NOTCH3, and NOTCH1 determined at day 1 and day 10 by RTqPCR. Results are expressed as fold change over day 1 IGG control, means ± SEM of n = 6 donors (two-way ANOVA, Dunnett's, and Sidak's post-test, $$p < 0.01, $$$p < 0.001 compared with respective treatment at day 1). (c) Representative photomicrographs of Bodipy (green) and DAPI (blue) stainings at day 10 (scale bar = 100 μm). (d) Quantification of Bodipy area per cell (left panel) and cell number (right panel) at day 10, results are expressed as fold change over day 10 IGG control, means ± SEM of n = 3 donors (one-way ANOVA, Dunnett's post-test). (e) mRNA levels of adipocyte markers (ADIPOQ, GPDH, PLIN1, and PPARG2) and brite adipocyte markers (UCP1, PGC1A, DIO2, CITED1, ELOVL3, PGC1B, TFAM, and CYCS) determined at day 10 by RTqPCR. Results are expressed as log2 fold change over IGG control, means ± SEM of n = 6 donors (two-way ANOVA, Dunnett's post-test). (f) Immuno-selected ScAT P1 progenitor cells were seeded on immobilized IGG control or NOTCH ligands JAG1 or DLL4 (colored as in a) and cultured in the presence of TGFβ1 during 4 days. (g) mRNA levels of HES1, NOTCH3, and NOTCH1 determined at day 1 and day 4 by RTqPCR. Results are expressed as fold change over day 1 IGG control, means ± SEM of n = 4 donors (twoway ANOVA, Tukey's post-test). (h) Representative photomicrographs of αSMA (green) and DAPI (blue) staining at day 4 (scale bar = 50 μm). (i) Quantification of cell number at day 4. Results are expressed as fold change over IGG, means ± SEM of n = 5 independent experiments (one-way ANOVA, Dunnett's post-test). (j) mRNA levels of myofibroblast markers (ACTA2, COL1A1, COL3A1, ELN, and INHBA) determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG, means ± sem of n = 4 donors (two-way ANOVA, Dunnett's post-test). *p < 0.05, **p < 0.01, ***p < 0.001 compared with IGG Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License NOTCH3 since the mRNA levels of NOTCH1 are not impacted and specific to replicative senescence compared with oxidative or DNA damage stress. The canonical Notch target genes HES1 and HEYL

  The present study clearly showed that the promotion of myofibrogenesis by Notch activity was observed even in the presence of exogenously added TGFβ, strongly suggesting additive distinct mechanisms. In agreement, the pharmacological inhibition of the TGFβ pathway did not alter the Notch-dependent activation of progenitor migration and myofibrogenesis. Notch activity in nonsenescent and in replicative senescent progenitors promoted the expression of SASP-related factors including SFRP4 and INHBA. In oncogene-induced senescence, the SASP induces a secondary senescence in surrounding cells that is mediated by Notch signaling[START_REF] Teo | Notch signaling mediates secondary senescence[END_REF]. Whether a similar impact is at play in the AT progenitors remains to be studied but is unlikely since Notch activation was associated with an inhibition rather than a stimulation of the senescent markers CDKN2A and CCDN1. NOTCH3 has already been F I G U R E 5 NOTCH-mediated promotion of myofibrogenesis is not dependent of the TGFβ pathway. (a) Representative photomicrographs of αSMA (green) and DAPI (blue) stainings in immuno-selected ScAT P1 progenitor cells seeded on immobilized IGG control (white) or NOTCH ligand DLL4 (pink) and cultured in basal medium (without TGFβ1) supplemented or not with gamma-secretase inhibitor LY411575 (LY: IGG gray; DLL4 light pink) during 4 days. (scale bar = 100 μm). (b) Quantification of cell number at day 4. Results are expressed as fold change over IGG, means ± SEM of n = 3 donors (one-way ANOVA, Tukey's post-test). (c) mRNA levels of myofibroblast markers (ACTA2, COL1A1, and COL3A1) determined at day 4 by RTqPCR. (d) Results are expressed as log2 fold change over IGG, means ± SEM of n = 7-11 donors two-way ANOVA, Dunnett's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 compared with IGG, $p < 0.05, $$p < 0.01, $$$p < 0.001 compared with DLL4). (d) Relative wound closure expressed as percentage of area over time of progenitor cells seeded on immobilized IGG control or DLL4, treated or not with gamma-secretase inhibitor LY411575, or in the presence of TGFβ1 (black), and subjected to scratch assay. Images were captured every 3 h during 69 h. The scratch area at time point 0 was set to 0. Values are means ± SEM of n = 3 donors, two-way ANOVA, Dunnett's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 (from time points 45-69) compared with IGG. (e) mRNA levels of epithelial-mesenchymal transition genes SNAI1 and SNAI2 determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG, means ± SEM of n = 7 donors (two-way ANOVA, Dunnett's post-test, ***p < 0.001 compared with IGG, $p < 0.05, $$p < 0.01 compared with DLL4). (f) Representative photomicrographs of NOTCH3 (red), DAPI (blue) and αSMA (green) stainings in progenitor cells seeded on IGG or DLL4 ligand with and without LY411575 at day 4 (scale bar = 20 μm). (g) mRNA levels of myofibroblast markers (COL1A1, COL3A1, and INHBA) in immuno-selected P1 progenitor cells seeded on IGG (white) or NOTCH ligand DLL4 (pink) and cultured in basal medium supplemented or not with TGFβ receptor inhibitor SB431542 (IGG + SB hatched white, DLL4 + SB hatched pink) during 4 days, determined by RTqPCR. Results are expressed as log2 fold change over IGG, means ± sem of n = 4 donors (two-way ANOVA, Tukey's post-test, *p < 0.05, **p < 0.01 compared with IGG, $$p < 0.01 compared with DLL4). (h) Relative wound closure (expressed as percentage of area) 72 h after scratch wound of progenitor cells seeded on DLL4 or treated with TGFβ1 (black) in the presence or not of SB431542 (TGFβ + SB hatched black). Values are mean ± SEM of n = 4 donors (one-way ANOVA and Sidak's post-test). (i) mRNA levels of myofibroblast markers (ACTA2, COL1A1, and COL3A1), epithelial-mesenchymal transition (SNAI1 and SNAI2) and premyofibroblast marker (NGFR) in immuno-selected ScAT P3 and P6 progenitor cells seeded on IGG control (white) or DLL4 (pink) and cultured in basal medium supplemented or not with gamma-secretase inhibitor LY411575 (LY: IGG gray; DLL4 light pink) during 4 days determined by RTqPCR. Results are expressed as log2 fold change over IGG, means ± SEM of n = 7 donors (two-way ANOVA, Tukey's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 compared with IGG, $p < 0.05, $$p < 0.01, $$$p < 0.001 compared with DLL4). (j) mRNA levels of senescence markers (CDKN2A and CCND1) in immunoselected ScAT P3 and P6 progenitor cells seeded on IGG control (white) or DLL4 (pink) and cultured in basal medium supplemented or not with dasatinib and quercetin (DQ; IGG + DQ light blue; DLL4 + DQ dark blue) during 4 days, determined by RTqPCR. Results are expressed as log2 fold change over P3 IGG, means ± SEM of n = 4 donors (two-way ANOVA, Tukey's post-test, *p < 0.05, **p < 0.01 compared with IGG, $p < 0.05 compared with DLL4). (k) mRNA levels of myofibroblast markers (ACTA2, COL1A1, COL3A1, and INHBA) determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG, means ± SEM of n = 4 donors (two-way ANOVA, Tukey's post-test, *p 0.05, **p < 0.01, ***p < 0.001 compared with IGG, $p < 0.05, $$p < 0.01, $$$p < 0.001 compared with DLL4).

  . We show that NOTCH3 protein, upon activation, localizes on fibers, a staining pattern that can be found within the Human Protein Atlas. While further investigation is required to conclude that the change in protein subcellular localization from membranes to fibers is responsible for cytoskeletal remodeling of myofibroblasts, it is associated with increased migratory capacity and expression of EMT transcription factors, SNAI1 and SNAI2. Our data show that the NOTCH3-dependent pathway is enriched in the -/CD271 + premyofibroblasts compared with the other cell subsets

F

  Native -/CD271 + premyofibroblasts accumulate in VsAT with senescence and are the target of the NOTCH3 pathway. (a) Percentage of SAβ-gal+ progenitors in ScAT and VsAT when donors were partitioned into tertiles by low, intermediate (int), or high SAβ-gal+ percentage in VsAT. Values represent means ± SEM of n = 38 donors in low, n = 39 in int and n = 39 in high VsAT senescence groups (two-way ANOVA and Tukey's post-test). (b) Number of progenitor cell subset per gram of ScAT and VsAT from patients in the low (white) and high (black) VsAT senescent tertiles from Figure 1e. Results are expressed as means ± SEM of n = 38 low and n = 39 high donors per group (two-way ANOVA, Tukey's post-test). (c) mRNA levels of NOTCH3 and HEYL in freshly isolated progenitor cell subsets (MSCA1 -/ CD271 -(-/-, blue), MSCA1-/CD271 + (-/CD271 + , NGFR + , light gray) premyofibroblasts and MSCA1 + (ALPL + , dark gray) preadipocytes) immuno-selected from ScAT. Results are expressed as means ± SEM of n = 7 donors (one-way ANOVA, Dunn's post-test). (d) Representative photomicrographs of NOTCH3 (red), αSMA (green) and DAPI (blue) stainings P1 in -/CD271 + and -/-progenitor subsets immuno-selected from ScAT, seeded on IGG control or NOTCH ligand DLL4, and cultured in basal medium during 4 days (scale bar = 50 μm). (e) mRNA levels of myofibroblast markers (ACTA2, COL1A1, COL3A1, ELN, and INHBA) and epithelial-mesenchymal transition markers (SNAI1 and SNAI2) in -/CD271 + and -/-progenitor subsets seeded on IGG control (-/CD271 + black, -/-white) or NOTCH ligand DLL4 (-/CD271 + pink, -/pink outline) determined at day 4 by RTqPCR. Results are expressed as log2 fold change over IGG -/CD271 + cells, means ± SEM of n = 5 independent experiments (two-way ANOVA, Dunnett's post-test, *p < 0.05, **p < 0.01, ***p < 0.001 compared with IGG TA B L E 2 Clinical and anthropometric parameters according to VsAT progenitor senescence

and NOTCH developmental pathways are markers of the senescence-associated secretory and intrinsic phenotypes of progenitors

were performed. VsAT progenitor secretome was mainly enriched in common canonical SASP factors including IGFBP7, IL6, and CXCL8 (cellular senescenceenriched reactome pathway), the CXCR2 Ligands (CXCL1, CXCL2, CXCL3, and CXCL8), as well as inflammatory, growth, and remodeling factors (MIF, FGF7, and INHBA) and factors of the complement and coagulation pathways (PLAT, PLAU, SERPINB2, E2 and E1, and TF; Table

1

).

3.2 | The BMP, WNT,

To investigate whether the VsAT progenitor senescence could be in part related to replicative growth pressure promoted by obesity, AT progenitors from nonobese individuals were submitted to serial passaging with low-density cell seeding. Due to the low amount of VsAT biopsies retrieved from nonobese individuals precluding immunoselection approaches, progenitors were immuno-selected from ScAT.

Gene Id p Value Ratio SASP Atlas SenMayo Irradiated preadipocytes Irradiated fibroblasts Protease inhibitor fibroblasts Inducible RAS Fibroblast

  Proteins were selected from available datasets (SASP atlas) as statistically upregulated by senescence stimuli in conditioned media.

									Irradiated Irradiated
	Gene Id Gene Id	p Value p Value	Ratio Ratio	SASP Atlas SASP Atlas				SenMayo SenMayo	Irradiated preadipocytes preadipocytes
	Gene Id	p Value	Ratio	SASP Atlas	Protease Protease	Inducible Inducible	Irradiated Irradiated Irradiated	SenMayo	preadipocytes
				Irradiated Irradiated	Protease inhibitor inhibitor	Inducible RAS RAS	Irradiated epithelial epithelial epithelial
				Irradiated fibroblasts fibroblasts	inhibitor fibroblasts fibroblasts	RAS Fibroblast Fibroblast	epithelial cells cells cells
	CPA3 INHBA POSTN	0.010986 0.000031 0.000015	0.80 338.34 0.24	fibroblasts +	fibroblasts +	Fibroblast +	cells	+	+
	ACE CREG1 ISLR PRG4	0.001953 0.00029 0.023438 0.00209	0.65 1.92 0.83 0.64
	ADAMTS1 CTHRC1 ITGBL1 PSAP	0.000427 0.006836 0.000977 0.026672	57.57 0.67 0.37 1.32	+ +	+	+ +
	ADAMTS5 CXCL1 ITIH4 PTGDS	0.03125 0.003845 0.020996 0.001068	0.82 6.44 19.22 268.45	+	+	+		+	+
	AEBP1 CXCL2 ITLN1 PXDN	0.044769 0.027344 0.000244 0.047913	0.88 1.83 1087.89 1.30	+ +	+ +	+ +		+
	AGRN CXCL3 KRT85 QSOX1	0.03125 0.008545 0.027344 0.001678	29.43 3.07 510.83 1.39	+ + +	+ + +	+ + +
	ALB CXCL6 LAMB1 RNASE4	0.003845 0.000092 0.000656 0.024414	1.96 735.04 1.65 0.79	+ +	+ +	+ + +		+
	ANXA2 CXCL8 LAMB2 S100A13	0.001678 0.000854 0.000381 0.000031	0.81 3.11 0.63 0.52	+	+ +	+ + +	+ +	+	+
	APCS CYR61 LBP SDC4	0.012207 0.038635 0.03125 0.001678	1.75 233.45 330.45 1.74		+	+
	APLP2 DCN LGALS1 SEPT8	0.005569 0.001343 0.000656 0.039795	2.25 0.60 0.74 1.27	+	+ +	+	+
	APOA1 ECM1 LGALS3 SERPINB2	0.00293 0.000031 0.000015 0.000107	55.76 0.44 0.54 2.75	+ +	+ +	+ + +	+
	APOC3 EMILIN2 LGALS3BP SERPINC1	0.009766 0.000076 0.039536 0.001068	1.60 2.12 1.47 125.93	+	+	+ +
	APOD ENPP2 LIF SERPINE1	0.000153 0.000488 0.000122 0.000015	0.52 0.39 402.14 3.30	+	+ +	+		+
	ARPC1A F2 LOX SERPINE2	0.03418 0.000061 0.003357 0.000504	22.82 195.33 58.52 2.39		+ +	+		+
	B4GALT1 F5 LOXL2 SERPINF1	0.028992 0.000214 0.023438 0.000031	1.39 32.05 0.84 0.43	+	+ + + +	+ +
	BGN FAM114A1 LTBP2 SERPING1	0.003159 0.03125 0.001007 0.030518	1.76 0.85 1.78 0.82		+ +	+ +
	C1QBP FBLN1 LTBP4 SFRP2	0.000381 0.000381 0.047913 0.038635	25.15 0.50 28.77 2.02		+	+ +
	C4A FBLN2 MASP1 SFRP4	0.007813 0.000381 0.007813 0.047913	2.19 0.59 0.58 83.82		+ +
	C4B FBN1 METRNL SLIT2	0.003906 0.000504 0.024414 0.007813	4.58 0.59 0.87 0.72		+	+
	C7 FGF7 MFAP5 SLPI	0.000031 0.001953 0.015625 0.010254	65.24 2.01 0.69 70.58					+
	CAB39L FGG MIF SOD3	0.000488 0.03125 0.000046 0.000015	0.44 1.44 1.69 0.25	+	+ +	+		+
	CALR FN1 MMP10 SPON1	0.000015 0.020157 0.001678 0.01825	1.96 0.79 0.56 2.53	+ +	+ +	+ +	+	+
	CCDC80 FST MMP14 STC2	0.00029 0.000092 0.029541 0.006714	2.35 0.41 1.98 1.84			+	+	+
	CD59 FSTL1 MMP3 TF	0.006653 0.001343 0.000015 0.002136	1.28 0.67 0.18 34.82		+	+ +		+	+
	CFD GALNT2 MMP9 TGFBI	0.000107 0.037109 0.003159 0.03479	0.44 48.98 45.56 28.33	+ +	+	+		+
	CFH GC MSLN TGFBR3	0.000031 0.003906 0.03125 0.026672	0.39 53.89 249.28 1.78	+	+	+
	CFI GGH MYDGF THBS1	0.000488 0.020996 0.003357 0.000153	230.90 0.87 1.48 2.35	+ +	+	+ + +
	CHI3L1 GNAS NAMPT THBS2	0.000122 0.005157 0.014999 0.000839	294.27 1.29 0.81 1.93	+	+	+ +
	CHID1 GREM1 NID2 TNXB	0.002441 0.000977 0.005859 0.000076	20.90 324.39 1.69 0.48	+		+
	CILP GSN NRP2 TPSAB1/	0.002441 0.000015 0.001953 0.000061	0.60 0.37 147.98 0.25	+	+	+	+
	CLEC3B HMCN1 OGN TPSB2	0.000031 0.013672 0.000122	0.25 0.75 2.59		+	+
	CMA1 HP PAM TXN	0.04187 0.010986 0.044312 0.001068	37.97 1.83 0.90 0.75			+
	COL12A1 HPX PAMR1 TYMP	0.000031 0.001678 0.01825 0.000015	0.50 48.49 1.75 0.26	+	+	+
	COL14A1 IGF2 PAPPA VCAN	0.003906 0.000061 0.000031 0.000046	0.60 2.42 2.51 0.55	+	+ +	+ +		+
	COL18A1 IGFBP3 PCOLCE VTN	0.010742 0.000015 0.007904 0.000763	23.76 24.82 0.74 1.82	+	+ + +	+	+	+
	COL1A1 IGFBP4 PCOLCE2 WISP2	0.000381 0.000504 0.000153 0.000061	0.65 2.79 0.57 0.25	+	+ +	+		+
	COL1A2 IGFBP7 PDGFRL YBX1	0.003845 0.000031 0.002441 0.030151	0.71 2.54 0.69 0.88	+ +	+ +	+		+
	COL3A1 IGHG1 PI3 Note:	0.000107 0.000214 0.044769	0.48 85.05 0.97		+
	COL5A2 IGHG3 PLAT	0.028992 0.023438 0.000031	0.91 22.28 972.35			+ +		+
	COL6A1 IGHG4 PLAU	0.00029 0.015625 0.000031	0.61 54.44 176.63	+ +	+	+ +		+
	COL6A2 IGKC PLG	0.000153 0.006653 0.013672	0.59 1.96 51.15	+	+ +	+
	COL6A3 IL6 PLXDC2	0.000153 0.000732 0.027344	0.45 93.41 41.60	+	+	+		+	+

TA B L E 1 Differentially expressed proteins in ScAT and VsAT secretomes, SASP atlas, SenMayo gene set and media from irradiated human preadipocytes 14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 9 of 24 BOULET et al. TA B L E 1 (Continued) (Continues) 14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TA B L E 1 (Continued) 14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 3.3 | The activity of Notch modulates the replicative SASP of human AT progenitors To further investigate the Notch-dependent pathway highlighted in the replicative senescent AT progenitor transcriptome, ScAT progenitors were submitted to additional senescence-promoting stimuli, including oxidative stress induced by H 2 O 2 treatment and DNA damage induced by doxorubicin or etoposide treatments. The marked upregulation of NOTCH3 transcript levels, detected by RTqPCR (confirming the RNA sequencing data), was only observed in

  Statistical analyses were performed using two-way ANOVA followed by Tukey's multiple comparisons test (ns nonsignificant).

		VsAT progenitor senescence
		Low		Int		High
	Number of patients	38		39		39
	Ratio male/female	0.12		0.08		0.11
	Diabetic (%)	18.5		18.0		15.5
		Mean	SD	Mean	SD	Mean	SD	Adj P low	Adj P low	Adj P Int
								versus	versus	versus
								Int	High	High
	Glucose (mmol/L)	5.8	1.5	5.9	1.5	5.8	1.2	ns	ns	ns
	HbA1c (%)	6.0	1.1	6.0	0.8	5.9	0.8	ns	ns	ns
	Triglycerides (mmol/L)	1.5	0.9	1.3	0.7	1.3	0.6	ns	ns	ns
	Cholesterol (mmol/L)	5.3	0.9	5.1	0.8	5.2	1.0	ns	ns	ns
	HDL (mmol/L)	1.2	0.3	1.2	0.3	1.1	0.2	ns	ns	ns
	LDL (mmol/L)	3.5	0.8	3.3	0.8	3.4	0.9	ns	ns	ns
	SGOT/ASAT (IU/L)	24.1	12.8	24.7	10.8	23.6	10.2	ns	ns	ns
	SGPT/ALAT (IU/L)	35.6	22.9	36.3	19.3	38.2	22.5	ns	ns	ns
	HOMA-IR	6.1	4.3	4.8	2.8	5.4	3.9	ns	ns	ns
	Waist-to-hip ratio	0.98	0.12	0.93	0.13	0.95	0.12	ns	ns	ns
	Age (years)	43.39	9.84	41.60	10.26	39.41	9.83	ns	0.0351	ns
	BMI (kg/m 2 ) at 20 years	28.22	6.96	30.02	7.46	32.27	8.40	ns	0.0307	ns
	Actual BMI (kg/m 2 )	43.23	4.56	44.47	6.06	45.06	7.05	ns	ns	ns
	Note:

14749726, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/acel.13776 by NATHALIE BOULET -Université Toulouse Iii Paul Sabatier , Wiley Online Library on [09/01/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License

Funding information

AVIESAN (Inserm/Sanofi R&D)Grant/Award Number: ARF20170938868;

DATA AVA I L A B I L I T Y S TAT E M E N T

All RNAseq datasets generated and used in this study will be deposited and available from the NCBI Gene Expression Omnibus (GEO) portal after the acceptance of the manuscript.

O RCI D

Nathalie Boulet

https://orcid.org/0000-0003-1011-3474

R E FE R E N C E S

progenitor senescence. One cannot exclude that other cell types, including adipocytes, endothelial cells, and/or macrophages may provide a stronger contribution than progenitors alone in the link between SAβ-Gal+ cell accumulation and adipocyte hypertrophy and/or metabolic impairment associated with obesity. Whether such a mechanism is also involved in aging remains to be established, especially since uncontrolled fibrosis is a common hallmark of aged tissues; referred to as "fibroageing" [START_REF] Selman | Fibroageing: An ageing pathological feature driven by dysregulated extracellular matrix-cell mechanobiology[END_REF]. We did not observe positive association between the accumulation of senescent progenitors and age but rather the inverse association; however, our cohort was not designed for the study of chronological aging but rather for the study of obesity-accelerated aging.

ACK N OWLED G M ENTS

We acknowledge the support of E. Riant (Genotoul TRI Cytometry), F.

CO N FLI C T O F I NTE R E S T

The authors declare no competing interests.

S U PP O RTI N G I N FO R M ATI O N

Additional supporting information can be found online in the Supporting Information section at the end of this article.

How to cite this article: Boulet, N., Briot, A., Jargaud, V., Estève, D., Rémaury, A., Belles, C., Viana, P., Fontaine, J., Murphy, L., Déon, C., Guillemot, M., Pech, C., Veeranagouda, Y., Didier, M., Decaunes, P., Mouisel, E., Carpéné, C., Iacovoni, J. S., Zakaroff-Girard, A. … Bouloumié, A. (2023).


S Kaushik

B Cerino

Y Yan

E Trouvé

L Ravanel

F Magnin

SAR COHERENCE MATRIX AS A TOOL TO UNDERSTAND BEHAVIOURS OF ICE APRONS

Keywords: InSAR coherence, TerraSAR-X, PAZ, Ice apron, Mont-Blanc massif

This paper focuses on understanding the temporal behaviour of Ice Aprons (IAs) in the Mont-Blanc massif using high resolution SAR coherence matrix. InSAR coherence is estimated between all possible pairs of TerraSAR-X images acquired in 2009 and 2011 as well as between PAZ images acquired in 2020, both at 11-day interval. The results show that coherence values in summer are higher in 2020 than in 2009 and 2011. Coherence matrices are also computed for different regions of a glacial system. The results are compared with those of IAs to understand the differences in their temporal and physical behaviours. In summer, all IAs show an increase in coherence values, while other glacier regions show very low or no coherence. This information could be useful for automatic classification methods, where IAs could be classified separately as a different class from the other types of glaciers.

INTRODUCTION

Glaciers in the Mont-Blanc massif (MBM) constitute a living subject in numerous studies using remote sensing [START_REF] Jauvin | Integration of corner reflectors for the monitoring of mountain glacier areas with sentinel-1 time series[END_REF] [START_REF] Prébet | A data-adaptive eof-based method for displacement signal retrieval from insar displacement measurement time series for decorrelating targets[END_REF], because they are considered as important indicators of water resources and climate change. An increase in temperature directly results in permafrost warming [START_REF] Magnin | Modelling rock wall permafrost degradation in the mont blanc massif from the lia to the end of the 21st century[END_REF] and usually increases glacier retreat. However, the local impact of global warming on the behaviour of ice aprons (IAs) is still not clear. The IAs are small ice features (less than 0.1 km 2 ) located on very steep slope (> 40 • ) and mostly in high altitude [START_REF] Guillet | Variations in surface area of six ice aprons in the mont-blanc massif since the little ice age[END_REF]. IAs correspond to likely oldest ice regions in the MBM and can thus be considered as a glacial heritage [START_REF] Guillet | Investigation of a cold-based ice apron on a high-mountain permafrost rock wall using ice texture analysis and micro-14c dating: a case study of the triangle du tacul ice apron (mont blanc massif, france)[END_REF]. The number of IAs in the MBM is significant, but studies for understanding these IAs are complicated because of their small size, difficult access and complex links to local climate variables [START_REF] Helfricht | Local extremes in the lidar-derived snow cover of alpine glaciers[END_REF]. In fact, all major global glacier inventories even fail to consider the IAs as a specific sub-class of glaciers and often show them as part of larger glacial systems [START_REF] Benn | Glaciers and Glaciation[END_REF]. As a result, very few IAs over the world have been studied. Initial definitions of IAs Corresponding author made the hypothesis that IAs are temporally stable ice bodies with no significant evolution along the year. But recent studies have shown a high sensitivity of IAs to climate change. [START_REF] Guillet | Variations in surface area of six ice aprons in the mont-blanc massif since the little ice age[END_REF] showed that IAs have been continuously losing their surface areas and thickness since the end of the Little Ice Age (LIA). But all previous studies have relied on historical photographs and recent high resolution optical images. Studies of IAs with advanced tools such as high resolution SAR images have never been attempted before and thus seem of particular interest.

In this paper, we aim to understand the temporal behavior of IAs in the MBM by means of high resolution SAR images. The interest of high resolution SAR images for studying IAs is twofold: 1) the high resolution (on the order of ≈ 2.5 m) allows efficiently capturing small areas covered by IAs; 2) SAR coherence matrix provides a useful way to survey the temporal evolution of targets under observation, since the coherence values constitute a relevant indicator of surface changes. We compute coherence matrices over IAs from TerraSAR-X images acquired in 2009 and in 2011 and PAZ images acquired in 2020. Since TerraSAR-X and PAZ have very similar acquisitions (in terms of wave frequency, revisit time, etc.), a joint analysis of both data sets enables us to consistently follow the temporal behaviors of IAs. Moreover, coherence matrices for other land classes in the glacial system such as accumulation zones, ablation zone, hanging glaciers, forest and urban areas are also computed in order to highlight the difference in behaviour of IAs compared to other glacier regions.

The main contribution of this paper lies on the first deployment of high resolution SAR images to understand temporal behaviors of IAs in the MBM, the considered targets being important for climate research but poorly studied until now. This study constitutes a preliminary step towards the physical interpretation of IAs. The paper is organised as follows: the study area and data processing are described in Section 2 and Section 3 respectively. Results and discussion are given in Section 4. Final conclusions are drawn in Section 5.

STUDY AREA

The MBM is spread over three countries, France, Italy and Switzerland. It is dominated by the Mont-Blanc summit (4809 m a.s.l) and composed of lots of glacier basins, but in this study we focus on the IAs spread across the entire massif. In the chosen study area, there are two main glaciers: Mer de Glace and Argentière glaciers (Fig. 1). The IAs are spread in the massif as shown in Fig. 1. The revisit time of TerraSAR-X and PAZ satellites is 11 days.

The shapefiles of all IAs in the MBM are obtained by accurately digitizing the boundaries on very high resolution orthophotos (0.2 m resolution). Due to geometrical distortions (e.g. layover, shadow and foreshortening) related to the specific SAR acquisition geometry, all IAs cannot be studied. Only IAs avoiding these distortions have been selected by using a visibility map built from the Digital Elevation Model (DEM) obtained from Pleiades stereo image pairs and the temporal mean of the 28 SAR images acquired by PAZ in 2020 [START_REF] Kaushik | Visibility Analysis of Glaciers on Steep Slopes in the European Alps using TerraSAR-X/PAZ Data[END_REF].

For each year and for each IA, coherence matrices are estimated between all image pairs of TerraSAR-X and of PAZ images. The coherence indicates the temporal correlation/decorrelation of IAs that is strongly related to stability/changes (as a result of melting or accumulation) of IAs' surface over time. A comparison is then performed between different years in order to highlight the IAs' surface changes over time, even though there are gaps between the three considered years due to data availability. Further, the aim is to compare the behaviours of IAs with those of other regions commonly associated with the mountain environment. For this, we focus on the PAZ data set acquired in 2020 (because of the regular acquisitions) and compute the coherence matrices for different land cover classes such as ablation zone, accumulation zone, urban area, forest and hanging glaciers.

RESULTS AND DISCUSSIONS

Coherence matrix comparison between different years

An example of the coherence matrix obtained for an IA located on the North face of the Aiguille d'Argentière with PAZ data set in 2020 is shown in Fig. 2. A seasonal effect is observed, i.e. the coherence values are much higher in the summer months (from the beginning of June to the beginning of September 2020) than in other periods of the year. This is related to the melting of the IA cover, leading to the exposure of bedrock surfaces below the IA. In other periods of the year, coherence is lost due to regular snow covers. These high coherence values in summer make it possible to perform further analysis (e.g. elevation change, movement detection) with Interferometry SAR. 3, that is to say, the coherence matrices are built between image pairs from June to September. From this comparison, it is safe to say that coherence values have globally increased in 2020 compared to in 2009 and 2011 (except for the IA "Tour"). High coherence is observed for the IA "Tour" for the entire period of observation. The IAs, "Argentière", "A Neuve" and "Jorasses", present high coherence in 2020 but not in 2009 and 2011. This increased summer coherence is interesting, a plausible explanation for this could be attributed to the exposure of rock surfaces beneath the IAs as a result of the melting in summers. This is consistant with the fact that IAs have been continuously losing their surface areas and thickness since the end of the little ice age. This could further be a strong indicator of the rapid melting of IAs as a result of the changing climate.

Comparison of coherence matrices for IAs and other land classes

Coherence matrices for different land classes, including IAs, glacier ablation and accumulation zones, urban areas, forest and hanging glaciers, obtained with PAZ data set in 2020 are shown in Fig. 4. The ablation and accumulation zones present similar behaviors and always present very low coherence along the year, because of continuous surface change in these areas. As expected, long term and seasonal correlation is observed for urban area and forest, due to permanently and seasonally stable features. Global low coherence is observed for hanging glaciers, but seasonal correlation can still be observed, coherence values being slightly higher in summer. Regarding IAs, those presented in this study, always show a higher coherence in summer and thus a relatively stable seasonal variation. Therefore, we can consider IAs, in general, as a separate class whose temporal behaviors are different from those of other zones in the glacial system, even though it happens that some IAs present low coherence along the year, similar to accumulation and ablation zones. Further investigations are necessary to relate the temporal behaviors of IAs to their physical characteristics such as location, orientation, morphology, etc. in order to better classify IAs and other glacial zones.

CONCLUSIONS

This paper deploys the high resolution SAR coherence matrix to understand the temporal behaviors of IAs in the MBM. According to the obtained results, we get the following conclusions: first, all IAs do not have the same temporal behaviors. Some of them stay weakly coherent over time, while others present high seasonal coherence. Besides the external climate conditions, their locations and orientations play an important part in their temporal evolution. Second, IAs do not always present temporal stability; they can present seasonal variations. In particular, in summer, high coherence is observed for a large number of studied IAs. This is related to the exposure of rock surfaces as IAs are melting. Considering that the thickness of IAs is of the order of a few meters, it is plausible that some IAs completely disappear in summer months and regain the mass again in winter. If this is the case, these ice features cannot be classified as IAs any more and further reconsideration of their definition needs to be contemplated. Third, different temporal behaviors of IAs from other land classes such as accumulation zones, ablation zones, hanging glaciers are observed. We can consider IAs as a separate class from other zones in a glacial system.

Future works include joint analyses of SAR coherence matrices and meteorological data (e.g. temperature, precipitation) in order to understand the physical behaviors of IAs and provide further evidences to prove their sensitivity to climate changes.

Fig. 1 .

 1 Fig. 1. Locations of the studied IAs in the MBM (in red). The background image is an ortho-photograph with 50 m resolution (source: IGN Geoportail).

  3. DATA PROCESSING Two high resolution X-band SAR image data sets are used for this study: 1. 51 TerraSAR-X images acquired in 2009 and in 2011, mostly during the 2 summer seasons, 2. 28 PAZ images acquired in 2020.

Fig. 2 .

 2 Fig. 2. Coherence matrix for the IA located on the North face of Aiguille d'Argentiere with PAZ data set in 2020. A value of 1 shows highest coherence, while values close to 0 show no coherence.

Fig. 3

 3 Fig. 3 presents the coherence matrices for 7 IAs (named by their location) in the years of 2009, 2011 and 2020. Since we were limited with continuous data availability for TerraSAR-X in 2009 and 2011, a comparison of only the

Fig. 3 .

 3 Fig. 3. Coherence matrix comparison for the years of 2009, 2011 and 2020 in case of 7 IAs. Each column corresponds to an IA named by its location.

Fig. 4 .

 4 Fig. 4. Coherence matrix for different land classes with PAZ data set. a) Ice aprons, b) Ablation zones, c) Accumulation zones, d) Urban areas, e) Forest, f) Hanging glaciers. The different matrices represent different locations in the study area.

Acknowledgement

The authors would also like to thank the German Aerospace Agency (DLR) for the TerraSAR-X images (Project MTH0232) and the Spanish Instituto Nacional de Tecnica Aerospacial (INTA) for the PAZ images (Project AO-001-051).