iPSCs-derived mesenchymal lineages from a MAD patient exhibited accelerated senescence
A previously reported male MAD patient was confirmed to carry the c.1579 C > T, p. R527C mutation in the LMNA gene (Fig. 1a). Isolated patient fibroblasts did not show the additional visible isoform of lamin A, though mutant cells exhibited earlier accelerated senescence, higher percentage of misshapen nuclear morphology (69.6 ± 9.3 % in MAD vs 10.8 ± 5.7 % in control, p = 0.0004) and abnormal epigenetic modifications (Fig. 1a and Supplementary Fig. 1a–j). The patient-specific iPSCs were generated using minicircle DNA as described previously36, and two independent clones were picked out for further validation (denoted as MAD-iPSCs #1 and #2). The two WT-iPSCs clones were generated from a single healthy individual as previously described36, and the WT-iPSCs and respective derivatives from WT-iPSCs were used as control throughout the study. No random integration of the minicircle vector was detected in these iPSCs (Supplementary Fig. 2a). Reverse transcription PCR and quantitative PCR (qPCR) showed comparable expression levels of pluripotency-associated genes in iPSCs and human ESCs H9 (Supplementary Fig. 2b, c). The bisulfite sequencing of endogenous OCT3/4 promoter region demonstrated rewriting of the DNA methylation after reprogramming (Supplementary Fig. 2d). The pluripotency and differentiation potential of these iPSCs were further confirmed by immunostaining and in vivo teratoma formation assay (Supplementary Fig. 2e, f). Karyotyping analysis also ensured the genome integrity in the iPSCs (Supplementary Fig. 2g).
a The pedigree of a MAD family and Sanger sequencing confirming the homozygous point mutation in LMNA (c.1579 C > T, p. R527C). b Immunostaining of lamin A/C (LMNA, green) in normal and MAD-patient derived dermal fibroblasts. DAPI, blue. Scale bar 10μm. The experiment was repeated three times with similar results. c Immunostaining of lamin A/C (LMNA, green), H3K9me3 (red), lamin B1 (LMNB1, green) and LAP2 (red) in WT-iPSCs and MAD iPSCs clones. DAPI, blue. Scale bar 10μm. The experiment was repeated three times with similar results. d Immunoblotting of lamin A/C (LMNA), lamin B1 (LMNB1), lamin B2 (LMNB2), EMERIN, LAP2, and WRN, KU70; HADC2, HP1a and FOXO3, PGC1a in dermal fibroblasts and two independent WT- and MAD- iPSCs clones. β-Actin was used as the loading control and only shown once as limited space. The experiment was repeated three times with similar results. e Representative images of lamin A/C (LMNA, green) and γ-H2A.X (red) co-immunostaining in passage 8 (P8) of WT and MAD-VSMCs with a corresponding statistical analysis. DAPI, blue. Scale bar 10 μm. Data are mean ± SD, the p value was calculated using two-tailed unpaired t-test, n = 6. Three independent differentiation experiments were performed with similar results. f Representative images of lamin A/C (LMNA, green) and γ-H2A.X (red) co-immunostaining in passage 12 (P12) of WT and MAD-VECs with a corresponding statistical analysis. DAPI, blue. Scale bar 10 μm. Data are mean ± SD, the p value was calculated using two-tailed unpaired t-test, n = 7. Three independentdifferentiation experiments were performed with similar results. g Representative images of Ki 67 (red) staining in WT-NSCs and MAD-NSCs at passage 20. Data are mean ± SD, the p value was calculated using two-tailed unpaired t-test, n = 4. Three independent differentiation experiments were performed with similar results. DAPI, blue. Scale bar 10 μm. Source data are provided as a Source Data file.
Next, we examined the nuclear integrity and aging-associated phenotypes in iPSCs. Lamin A/C was barely detectable in MAD-iPSCs, whereas lamin B1 was restored (Fig. 1c, d and Supplementary Fig. 3b). The decreased expression of lamin B2, LAP2, WRN, Ku70, FOXO3a, PGC1α, HP1α, and HDAC2 were all restored in MAD-iPSCs (Fig. 1d and Supplementary Fig. 3a). Furthermore, nuclear dysmorphology was rescued and proliferative capability was restored in MAD-iPSCs (Supplementary Fig. 3a and 1i). These data collectively indicated that premature senescence in MAD fibroblasts was rejuvenated in the pluripotent state.
To recapitulate the tissue-specific defects of MAD, we differentiated MAD-iPSCs into multiple lineages, including vascular smooth muscle cells (VSMCs), vascular endothelial cells (VECs), and neural stem cells (NSCs). The differentiated MAD-VSMCs, marked by Calponin, smooth muscle alpha-actin (αSMA), and smooth muscle 22α (SM22α) (Supplementary Fig. 4d–f, j), exhibited a remarkable increase in nuclear deformation (90.6 ± 13.7% in MAD-VSMCs vs 2.0 ± 5.9% in controls; p < 0.0001) and elevated DNA damage at passage 5 (90.0 ± 10.9 % in MAD-VSMCs vs not detectable in controls; p < 0.0001) (Fig. 1e). MAD-VECs, marked by von Willebrand factor (VWF) and endothelial nitric oxide synthase (eNOS) and validated by the Ac-LDL up-taking function (Supplementary Fig. 4g–i, j), manifested significantly elevated frequencies of nuclear blebbing (78.3 ± 7.2% in MAD-VECs vs 12.9 ± 5.0% in WT-VECs; p < 0.0001) and DNA damage (85.40 ± 7.42% in MAD-VECs vs 23.39 ± 6.11% in WT-VECs; p < 0.0001) (Fig. 1f). The NSCs generated from MAD-iPSCs were validated by sphere culture and expression of NESTIN, PAX6, and SOX2 (Supplementary Fig. 4a–c, j). No significant differences were observed either in the differentiation efficiency between MAD-iPSCs and WT-iPSCs or in the proliferative capability within 20 passages between MAD-NSCs and WT-NSCs (Fig. 1g and Supplementary Fig. 4c). Taken together, these data revealed defects in multiple lineages in this MAD patient as a result of the LMNA p.R527C mutation. The compromised vascular system was in line with the clinical features such as high blood pressure and atherosclerosis that are observed in MAD6,37.
MAD-MSCs recapitulated accelerated cellular senescence
Stem cell decline38 is an essential contributor to many age-related morbidities39,40. The deterioration of vascular cells in MAD prompted us to examine the progenitor/stem cells, particularly the MSCs. The MSCs we generated satisfied the criteria of surface markers and tri-lineage differentiation capability (P5 MSCs) (Fig. 2a and Supplementary Fig. 5a, b). The MAD patient iPSCs-derived MSCs(hereafter referred to as MAD-MSCs) exhibited a shorter cellular lifespan, impaired proliferative capability, and accelerated senescence (P13 MSCs) (Fig. 2b–d), which were accompanied by the upregulation of cell cycle arrest genes p16 and INK4b as well as the activation of senescence-associated inflammasome (CXCL1, VEGFA, IL6, IL8, PAI, BMP2, PAI and BMP2) (P13 MSCs) (Supplementary Fig. 6c, d). As expected, MAD-MSCs manifested increased nuclear blebbing and DNA damage (P13 MSCs) (Fig. 2e and Supplementary Fig. 6b, e). Of note, MAD-MSCs exhibited enlarged nuclei (Fig. 2g, h and Supplementary Fig. 6f). Transmission electron microscopy (TEM) revealed a loss of peripheral heterochromatin in P13 MAD-MSCs (Fig. 2f). Furthermore, there was a significant increase in the percentage of mitochondrial damage in P13 MAD-MSCs (22.6% in MAD-MSCs vs 4.1% in WT-MSCs, p < 0.0001) (Fig. 2f). These data indicated MSCs from the MAD patient recapitulated accelerated cellular senescence.
a, Human MSCs derived from WT and MAD-iPSCs by a temporal neuralized ectoderm induction method. b Growth curve of MSCs. Bars represent the mean ± SD.; n = 3 independent biological replicates; ***p < 0.001; n.s., non-significant; p value was calculated using two-way ANOVA test. c Proliferative capability measured by Ki 67 (red) using P13 MSCs. DAPI, blue. Scale bar 10 μm. Data represent the mean ± SD, n = 5. d SA-β-gal staining of MSCs at passage 13; Scale bar 100 μm. Data are mean ± SD, n = 3. e Representative image of γ-H2A.X (red) immunostaining at passage 13. DAPI, blue. Scale bar 10 μm. Data are mean ± SD, n = 8. The p values were calculated using two-tailed unpaired t-test. Experiments in c-e were repeated three times with similar results. f Representative transmission electron micrographs (TEM) of P13 WT- and MAD-MSCs. Scale bar 250 nm. The percentage of damaged mitochondria was quantified and calculated in MSCs. Data are mean ± SD, n = 462 WT, n = 368 MAD. The p value was calculated using two-tailed unpaired t-test. Three independent replicates were performed with similar results. g Representative images of co-staining of lamin B1 (LMNB1, green) and HP1a (red), lamin A/C (LMNA, green) and LAP2 (red), lamin A/C (LMNA, green) and H3K9me3 (red), lamin A/C (LMNA, green) and H3K27me3 (red), lamin A/C (LMNA, green) and H3K27ac (red), and lamin A/C (LMNA, green) and H3K4me3 (red) in passage 9 MSCs. DAPI, blue. Scale bars 10 µm. h Fluorescence intensity of g were quantified, including Lamin B1 and HP1a (WT n = 189, MAD n = 79), lamin A/C and LAP2 (WT n = 84, MAD n = 51), H3K9me3 (WT n = 88, MAD n = 64), H3K27me3 (WT n = 71, MAD n = 31), H3K27ac (WT n = 163, MAD n = 55), H3K4me3 (WT n = 145, MAD n = 79) and nuclei size (WT n = 293, MAD n = 143). Data are mean ± SD; the lines in scatter dot plot indicate the averaged intensity and the p values were calculated using two-tailed unpaired t-test. Three independent biological experiments were performed with similar results. i GO and KEGG enriched signaling pathways in MAD-MSCs. All p-values were determined by two-sided modified Fisher’s exact test using DAVID. j Comparison of aging-associated gene profilings between MAD-MSCs and other human MSCs aging models. Color depth indicates the level of transcriptional similarity. Source data are provided as a Source Data file.
To investigate early epigenetic changes behind MAD-MSCs aging, we examined the nuclear integrity and histone modifications at P9 when MAD-MSCs have not yet undergone senescence (Fig. 2b and Supplementary Fig. 6a). Significantly decreased lamin B1 and H3K9me3 were shown in MAD-MSCs compared with the control (Fig. 2g, h). Although the loss of LAP2a and HP1a were observed in multiple senescence conditions and MAD fibroblasts (Fig. 1d), significant changes in neither protein were observed in MAD-MSCs at P9 (Fig. 2g, h), but appeared at late passage P13 (Supplementary Fig. 6f). This suggests that loss of LAP2a and HP1a were not the initial response for senescence in MAD scenario. In addition, H3K9m3/H3K27me3-enriched heterochromatin budded off from the nuclei in MAD-MSCs (Supplementary Fig. 6e), which was in line with previous reports in different human MSCs senescence models41,42. Strikingly, the active histone markers H3K4me3 and H3K27ac were also found in regions of the budded nucleus and were even at times scattered in the cytoplasm (Supplementary Fig. 6e), reflecting the dramatically disorganized nucleus in MAD-MSCs. These findings suggested that accelerated stem cell senescence in this MAD patient could be a consequence of collapsed homeostasis in the nucleus.
Transcriptome comparison between MAD-MSCs and other human MSCs aging models
To investigate the potential contributors to MAD-MSCs senescence, RNA-seq was performed and compared between MAD-MSCs and WT-MSCs derived from the WT-iPSCs both at P9. Overall, 1488 genes were downregulated, while 1447 were upregulated in MAD-MSCs (two-fold change, p < 0.05) (Supplementary Fig. 7a, b; Supplementary Data 3). GO term analysis revealed the enrichment of extracellular matrix (ECM) organization (n = 39, p = 6.59E-10), negative regulation of cell proliferation (n = 49, p = 1.50E-05), cell cycle arrest (n = 21, p = 6.57E-04), cytoskeleton organization (n = 26, p = 3.29E-05) and inflammatory response (n = 43, p = 3.65E-04) in the upregulated genes, while notch signaling pathway (n = 19, p = 1.10E-04), transcription factor binding/activity (n = 80, p = 8.40E-04), angiogenesis and cancer-associated pathways were enriched in the downregulated genes (Fig. 2i). Interestingly, analysis of genetic assoicated diseases (GAD) database revealed that genes associated with cardiovascular disorders and metabolism disturbance were enriched in MAD-MSCs (Supplementary Fig. 7c, d).
To explore the similarities and differences between MAD-MSCs and other senescence models, we cross-analyzed 26 aging hMSCs transcriptomic datasets, including 20 premature senescent hMSCs and 6 senescence-delayed hMSCs models, termed ‘accelerated hMSCs’ and ‘alleviated hMSCs’, respectively (Supplementary Fig. 8a). Senescence, a process of cellular deterioration marked by chronic loss of homeostasis in macromolecules, is associated with increased expression of senescence-promoting genes and decreased expression of anti-senescence-associated genes. Based on this assumption, we defined the upregulated genes in senescent hMSCs and downregulated genes in alleviated hMSCs as senescence-associated genes, whereas the downregulated genes in senescent hMSCs and upregulated genes in alleviated hMSCs as geroprotection-associated genes (Supplementary Fig. 8b, c). The intersection of these gene sets revealed that different hMSCs aging models exhibited distinct transcriptional profiles and clustering of some datasets, indicating the aging process is complicated while interconnected (Fig. 2j). Notably, MAD-MSCs exhibited the highest transcriptional similarity to bone marrow-derived hMSCs undergoing replicative aging (Fig. 2j and Supplementary Fig. 8d).
LADs reorganization in MAD-MSCs
LADs reorganization has been reported in several laminopathy-based disorders, varying by cell-context20,23,43,44. It is well known that loss of lamin B1 is a biomarker of senescence, and lamin B1 LADs reorganization is involved in various aging models45,46. We performed both lamin A/C and lamin B1 chromatin immunoprecipitation and sequencing (ChIP-Seq) in WT and MAD-MSCs (MSCs at P9-P11). The lamin A/C LADs (A-LADs) and lamin B1 LADs (B-LADs) were identified by Enriched Domain Detector47 and further classified into three categories, e.g. loss, overlap, and gain, according to the specific change of genomic regions in MAD-MSCs when compared with WT-MSCs (Fig. 3a). Genome-wide comparison showed an increased number of both A- and B-LADs (237 lost vs 628 gained in A-LADs; 274 lost vs 295 gained in B-LADs) in MAD-MSCs (Fig. 3d, e). The genomic coverage of A-LADs increased dramatically from 94 Mb in WT-MSCs to 217 Mb in MAD-MSCs, whereas the B-LADs coverage was slightly decreased (293 Mb in WT-MSCs vs 268 Mb in MAD-MSCs) (Fig. 3b). Of note, the enrichment strength of both A- and B-LADs decreased significantly in MAD-MSCs (Fig. 3c). Overall, 865 differential A-LADs and 569 differential B-LADs were identified in MAD-MSCs compared with WT-MSCs (Fig. 3d, e).
a Representative distribution of LADs at specific genome loci in WT and MAD-MSCs, including A-LADs and B-LADs. b The length of genomic coverage of A-LADs and B-LADs in WT and MAD-MSCs. c Boxplot showing Lamin enrichment in WT A-LADs (n = 340), MAD A-LADs (n = 535), WT B-LADs (n = 257), and MAD B-LADs (n = 326), with 2 biological replicates for lamins ChIP-seq. Box plots display the median as the center line, the 25th and 75th percentiles as the bounds of the box, and the whiskers represent the minimum and maximum values within 1.5 times the interquartile range from the lower and upper quartiles. All p-values were determined using the two-sided Wilcoxon rank-sum test. d, e Heatmap of differential A-LADs and B-LADs in WT and MAD-MSCs. f Differentially expressed genes associated with LADs reorganization. Genes with over 2-fold transcriptional changes were counted. g Cross-analysis of the enrichment of dysregulated genes due to LAD reorganization in MAD-MSCs with geroprotection/senescence-associated profile in different hMSCs aging models. Color depth indicates enrichment score.
To further investigate the effects of LADs reorganization on transcriptional regulation, we integrated the transcriptome with differential LADs. Overall, 253 genes were dysregulated in reorganized A-LADs, while 318 were found in B-LADs (Fig. 3f; Supplementary Data 4). Notably, the gained LADs were associated with the majority of the transcriptomic changes when compared to the lost regions (221 genes in gained A-LADs vs 32 genes in lost A-LADs; 235 genes in gained B-LADs vs 90 genes in lost B-LADs) (Fig. 3f; Supplementary Data 4). To further evaluate the effect of LADs reorganization on MSCs aging, the dysregulated genes were cross-analyzed with senescence/geroprotection-associated gene profiles in hMSCs aging models. The expression changes observed in this MAD case, potentially mediated by LAD reorganization, were co-enriched with a variety of hMSCs models, especially normal old hMSCs and HGPS-MSCs (Fig. 3g). Notably, the gained LADs-associated genes were dominant for the co-enrichment of senescence- and geroprotection-associated profile (Fig. 3g).
For example, we observed a correlation between the downregulation of HDAC4, a gene associated with geroprotection48, and the gain of A-LADs in MAD-MSCs (2.6-fold decrease, FDR = 1.17e-38)(Supplementary Fig. 9a). CDK18, a cell cycle checkpoint factor safeguarding genome integrity49, was repressed in MAD-MSCs as it fell into the gained A-LADs (12.5-fold decrease, FDR = 3.20e-155) (Supplementary Fig. 9a). Similarly, several potential geroprotection-associated genes, including FOXC1 (22.5-fold decrease, FDR = 0), RNF130 (22.5-fold decrease, FDR = 0), ZNRF2 (6.2-fold decrease, FDR = 3.02E-68) and PRMT3 (22.5-fold decrease, FDR = 0), were downregulated as a result of gain of LADs (Supplementary Fig. 9a). Interestingly, lineage associated genes were also found to be dysregulated as LADs reorganization. Neural-related NEDD9 (4.1-fold increase, FDR = 1.50E-82), ANXA1 (2.6-fold increase, FDR = 1.13E-59), ANXA6 (2.1-fold increase, FDR = 1.13E-59), and immune-related IL7R (5.9-fold increase, FDR = 2.53E-121) and TRBC2 (5.1-fold increase, FDR = 6.32E-24), were found to be abnormally activated as a result of loss in LADs (Supplementary Fig. 9a). The data collectively suggest an association between extensive reorganization of LADs and altered expression profiles of genes that are involved in aging and lineage specification in MAD-MSCs.
Reposition of non-LAD lamina-chromatin binding peaks participated in aging-associated gene regulation in MAD-MSCs
When interpreting lamina-chromatin interactions, we identified many non-LAD lamina-chromatin binding peaks, termed ‘peaks out of LAD’, that were dispersed outside of LADs (Fig. 4a). Strikingly, there were a total of 1959 peaks out of A-LADs in WT-MSCs and 9442 peaks out of A-LAD in MAD-MSCs, with only a small portion (637 peaks) overlapping (Fig. 4b). Likewise, 636 and 1494 peaks out of B-LADs were identified in WT-MSCs and MAD-MSCs respectively, with only 139 shared peaks (Fig. 4b). To further investigate the potential function of these non-LAD lamina-chromatin interaction peaks, genome-wide co-occurrence between non-LADs lamina-chromatin binding peaks and promoters were analyzed. Notably, non-LADs peaks were not randomly repositioned but rather co-occurred with the promoter (permutation test, p = 0) (Fig. 4c), suggesting that non-LAD peaks were likely involved in transcriptional regulation. Indeed, a total of 569 differential genes fell into the repositioned non-LADs peaks in MAD-MSCs (Fig. 4d; Supplementary Data 4). Among these genes, the gained peaks out of A-LADs accounted for the majority of the changes (401 genes, 77.1%), while the gained peaks out of B-LADs contributed 16.0% (91 genes) to the changes (Fig. 4d). These dysregulated genes were further cross-analyzed based on senescent and geroprotective gene profiles to evaluate the co-enrichment between repositioned non-LADs peaks and senescence. Notably, the gained peaks out of A-LADs exhibited the highest enrichment in upregulated senescence-associated genes and downregulated geroprotection-associated genes across the different hMSCs aging models (Fig. 4e).
a Distribution of non-LADs lamina-chromatin binding peaks at specific genome loci in WT and MAD-MSCs. Each vertical bar represents one peak out of LADs. b Global non-LAD lamina-chromatin binding peaks identified in WT and MAD-MSCs. The number of the peaks are indicated. c Genome-wide co-occurrence of non-LAD lamina-chromatin binding peaks with promoters using a one-sided permutation test. The vertical axis density represents the frequency of co-occurrence of non-LAD binding peaks with promoters while horizonal axis represents predicted co-occurrence number. The observed co-occurrence number are indicated. d Differentially expressed genes associated with repositioned non-LADs lamina-chromatin binding peaks in MAD-MSCs Genes with over 2-fold transcriptional changes were counted. e Cross-analysis of enrichment of dysregulated genes due to reposition of non-LAD lamina-chromatin binding peaks in MAD-MSCs with geroprotection/senescence-associated profile in different hMSCs aging models. Color depth indicates the enrichment score.
TBX2, an indispensable transcription factor for early development and geroprotection50, showed decreased expression in MAD-MSCs, corresponding to the increased lamina-chromatin binding peaks in MAD-MSCs (5.1-fold decrease, FDR = 1.09E-226) (Supplementary Fig. 10a). DCP2, a protein responsible for mRNA decapping, RNA decay and closely associated with the aging process51,52, was downregulated in MAD-MSCs, possibly due to the gained lamina-chromatin binding peak in its promoter (2.1-fold expression decreases, FDR = 9.17E-27) (Supplementary Fig. 10a). Similarly, CEP70, a centrosomal protein critical for microtubules organization during mitosis, was downregulated in MAD-MSCs, which could be attributable to the gained LAD and lamina-chromatin binding peak at its promoter (2.7-fold decrease, FDR = 1.57E-33) (Supplementary Fig. 10a). Interestingly, several lineage specific genes, including NNAT (5.2-fold increase, FDR = 3.45E-60) and NAV2 (2.8-fold increase, FDR = 1.01E-82), were also abnormally activated in repositioned lamina-chromatin binding peaks (Supplementary Fig. 10a). These observations suggest that in addition to LADs reorganization, the repositioning of non-LAD lamina-chromatin binding peaks may also be associated with changes in transcriptional regulation, potentially influencing MAD-MSCs senescence and aspects of progeroid pathogenesis.
Lamina-chromatin interaction coordinated with chromatin features to regulate transcription in MAD-MSCs
To explain transcriptional upregulation in the gained lamina-chromatin interaction sites and transcriptional downregulation in the lost lamina-chromatin binding regions (Figs. 3e and 4e), we integrated multiple profiling data, including active marks A transposase-accessible chromatin with sequencing (ATAC-Seq) and H3K27ac ChIP-Seq as well as repressive marks H3K9me3 and H3K27me3 ChIP-Seq, to examine the contribution of chromatin features to the transcriptional dysregulation in MAD-MSCs compared to WT-MSCs (Fig. 5a). ATAC-Seq revealed a more open chromatin state in MAD-MSCs with 45,906 lost peaks and 93,844 gained peaks (FDR < 0.05) (Fig. 5b). Consistently, H3K27ac ChIP-Seq identified 21,349 lost peaks and 37,770 gained peaks in MAD-MSCs, corresponding to 31,478 inactivated typical enhancers (TEs), 188,270 activated TEs, 560 inactivated and 264 activated super-enhancers (SEs) (Fig. 5e and Supplementary Fig. 11c-g). Globally, the ATAC signals were mainly located in intron (48%) and intergenic regions (41%). About 20% of ATAC was associated with the enhancer, and 11% occurred at LADs (Supplementary Fig. 11a, 11h). Of note, 22% of the lost ATAC peaks in MAD-MSCs were enriched at promoter regions and more than half were mapped to the enhancer regions, especially SEs (46%) (Supplementary Fig. 11h). Meanwhile, 11% of gained ATAC peaks in MAD-MSCs were associated with enhancers (Supplementary Fig. 11h). In lost ATAC peaks, 6% were mapped to A-LADs and 9% was mapped to B-LADs. In the gained ATAC peaks, 4% were mapped to A-LADs and 12% to B-LADs (Supplementary Fig. 11a). About 9% of gained ATAC fell in lamin B1-specific LADs, in contrast to 1% in LAMIN A-specific LADs (Supplementary Fig. 11a). The altered enhancers in MAD-MSCs exhibited a pattern similar to that of ATAC in the distribution of lamin A/C- and lamin B1-LADs (Supplementary Fig. 11a, b). Interestingly, the enriched ATAC motifs in MAD-MSCs were highly matched with the pioneer transcriptional factors binding regions enriched in HGPS fibroblasts53 (Supplementary Fig. 11i). When integrated with transcriptomic profiling, it was noted that ATAC and H3K27ac signals were significantly higher in the promoter regions of upregulated genes compared with the promoter regions of downregulated genes, regardless of the lamina-chromatin interaction states (Figs. 5c, d, 5f, g).
a Representative distribution of different chromatin features in lamina-chromatin binding sites. b Overall view of ATAC peaks redistribution in MAD-MSCs. c Averaged chromatin accessibility in promoter regions with different A and B-LADs reorganization. d Averaged chromatin accessibility in the promoter region with different non-LAD lamina-chromatin binding peaks. e Overall view of H3K27ac peaks redistribution in MAD-MSCs. f Averaged H3K27ac peaks in promoter regions with different A and B-LADs reorganization. All p-values were determined using the two-sided Wilcoxon rank-sum test. g Averaged H3K27ac peaks in promoter regions with different non-LAD lamina-chromatin binding peaks. All p-values were determined using the two-sided Wilcoxon rank-sum test. h Overall view of H3K27me3 redistribution in MAD-MSCs. i Averaged H3K27me3 peaks in the promoter regions with different A and B-LADs reorganization. All p-values were determined using the two-sided Wilcoxon rank-sum test. j Averaged H3K27me3 peaks in promoter regions with different non-LAD lamina-chromatin binding peaks. All p-values were determined using the two-sided Wilcoxon rank-sum test. k Overall view of H3K9me3 redistribution in MAD-MSCs. l Averaged H3K9me3 peaks in promoter regions with different A and B-LADs reorganization. All p-values were determined using the two-sided Wilcoxon rank-sum test. m Averaged H3K9me3 peaks in promoter regions with different non-LAD lamina-chromatin binding peaks. All p-values were determined using the two-sided Wilcoxon rank-sum test.
In parallel, H3K27me3 peaks and H3K9me3 signals were also found to be increased (13,751 lost vs 21,219 gained and 9059 lost vs 29,085 gained, respectively) in MAD-MSCs (Fig. 5h, k), with a distribution pattern that differs to ATAC and H3K27ac peaks (Supplementary Fig. 11j–k). Interestingly, H3K27me3 and H3K9me3 signals were significantly higher in the promoter regions of down-regulated genes compared with the promoter regions of up-regulated genes, which is independent of the lamina-chromatin interaction states (Figs. 5i–j, 5l–m).
The lower signals of ATAC and H3K27ac and higher H3K27me3 signals in HDAC4 and CDK18 gene loci may explain the downregulation of geroprotection-associated HDAC4 and CDK18 within gained A-LADs in MAD-MSCs (Supplementary Fig. 12a). Similarly, down-regulation of ZSCAN12 (2.8-fold decrease, FDR = 4.74E-16) and DHRS3 (42.3-fold decrease, FDR = 1.93E-292) were observed in gained B-LADs with lower signals of ATAC and H3K27ac and higher signals of H3K9me3 and H3K27me3 (Supplementary Fig. 12b). On the other hand, loss of A-LADs occupancy in NEDD9 locus with higher ATAC and H3K27ac signals at the promoter region may have contributed to the activation of a lineage specific gene (Supplementary Fig. 12a). Lower signal of repressive marks and higher signal of active marks enriched in the lost LADs resulted in up-regulation of NTM (27.1-fold increase, FDR = 0) and NEK7 (5.2-fold increase, FDR = 4.93E-266) (Supplementary Fig. 12c). The PDGFA locus, located in the gained LAD in MAD-MSCs with a 4.9-fold increase in transcription (FDR = 4.53E-93), exhibited a higher signal of ATAC and H3K27ac but lower signal of H3K9me3 (Supplementary Fig. 12d). In the FBXO4 locus, the lower active marks explained why FBXO4 expression decreased in MAD-MSCs (2.5-fold decrease, FDR = 9.38E-28) even though LAD occupancy was lost (Supplementary Fig. 12d). The regulation of transcription by integrated chromatin features were also observed in genes located around non-LADs lamina-chromatin binding peaks, such as KAT2B, MYO6, SMAD2 and HIPK2 (Supplementary Fig. 13). Taken together, these observations suggest the transcription landscape observed in MAD-MSCs could be a coordinated action of lamina-chromatin interaction state and specific local chromatin features.
Hierarchical chromatin disorganization potentially shapes stem cell aging
Given that nuclear lamins facilitate the establishment of high-order chromatin architecture19,24, we then interrogated the chromatin conformation change in MAD-MSCs. Hi-C was performed with two biological replicates for each sample (Supplementary Fig. 14a), the statistics of the relevant datasets were summarized in Supplementary Data 7, and high-resolution of chromosome conformation was obtained (Supplementary Fig. 14c). In MAD-MSCs, an increase in short-distance interaction frequency and a decline in long-distance interaction frequency were observed (Supplementary Fig. 14b). While clear segregation of compartment A and B was observed in WT-MSCs, the separation became largely indistinct in MAD-MSCs (Fig. 6a and Supplementary Fig. 15). Saddle plot analysis indicated a global loss of compartmentalization, quantifying the strength of chromatin compartment based on the interaction frequencies arranged by eigenvector. The interactions of compartment A-B and B-B were increased, while the interactions of compartment A-A were decreased in MAD-MSCs (WT_AA:1.266, MAD_AA:1.109; WT_BB:1.270, MAD_BB1.308; WT_AB:0.707, MAD_AB:0.796) (Fig. 6b). When lamins-associated chromatin was analyzed, the interactions of the lamin-binding chromatins were significantly decreased in MAD-MSCs (Fig. 6c), suggesting that MAD mutation in LMNA possibly impairs high order chromatin organization and compartmentalization through jeopardized the chromatin interaction. Additionally, we observed 4.66% of compartment A converted to B and 14.36% of compartment B switched to A, in addition to the compartmental strengthening and weakening (Supplementary Fig. 14d). The higher percentage of compartment B to A switching was consistent with chromatin features observed in MAD-MSCs, including increased ATAC and H3K27ac marks.
a Normalized heatmap of specific region (q arm of chromosome 1) in WT and MAD-MSCs. The color maps of relative interaction probability in WT-MSCs and MAD-MSCs were displayed on the same scale. The A and B compartments were defined by PC1 signal (positive PC1 regions in red color represent A compartments, negative PC1 regions in blue color represent B compartments). b Statistical analysis of compartment interaction between compartment A and compartment B in WT-MSCs and MAD-MSCs according to Saddle plot analysis. c Analysis of the lamina-compartment interactions. d Boxplot showing length of WT TADs (n = 3823) and MAD TADs (n = 4001), with 2 biological replicates for Hi-C. Box plots display the median as the center line, the 25th and 75th percentiles as the bounds of the box, and the whiskers represent the minimum and maximum values within 1.5 times the interquartile range from the lower and upper quartiles. All p-values were determined using the two-sided Wilcoxon rank-sum test. e Overall view of TAD number in WT-MSCs and MAD-MSCs. f Category of differential TADs number presented in MAD-MSCs, including stable, shortened, shifted without change in length, and enlarged. g Overall view of CTCF redistribution in MAD-MSCs. h The distribution of CTCF across lamin-chromatin interaction sites. i Overall view of altered chromatin features, including CTCF binding, ATAC, H3K27ac, H3K27me3, H3K9me3, and gene expression in TADs. All p-values were determined using the two-sided Wilcoxon rank-sum test. j Integrative analysis of TAD disorganization and chromatin features in genomic region covering a dysregulated aging-associated gene, SETDB2, in MAD-MSCs. k Cross-analysis of the enrichment of dysregulated genes resulted from shortened TADs in MAD-MSCs with geroprotection/senescence-associated profile in hMSCs aging models. Color depth indicates enrichment score.
TopDom54 analysis revealed 3823 and 4001 TADs in WT-MSCs and MAD-MSCs, respectively (Fig. 6e). The increased TAD number in MAD-MSCs was accompanied by a shorter TAD length (725 kb on average in WT-MSCs vs 683 kb on average in MAD-MSCs) (Fig. 6d). The differential TADs were subsequently classified into three categories, with a significant portion of TADs (627) being either shortened (15.67%), shifted without length change (0.87%) or enlarged (4.27%), despite of 79.18% of stable structured TADs (FDR < 0.05) (Fig. 6f). CCCTC-binding factor (CTCF) is a core factor for TAD boundary maintenance and CTCF ChIP-Seq revealed the increased CTCF binding peaks in MAD-MSCs (Fig. 6g). The increased CTCF tended to bind at the A-LADs and B-LADs lost regions in MAD-MSCs which aligned with the boundaries of gained TADs (p = 0.0048) (Supplementary Fig. 16a), indicating that the mutant lamin A/C may contribute to TADs separation in MAD-MSCs. To further investigate the relationship between TADs reorganization and senescence, chromatin features and transcriptomic profiles were integrated with TAD structure. Notably, remarkable changes in ATAC, H3K27ac, CTCF binding, H3K9me3, as well as transcription were all observed in the shortened TADs (Fig. 6i). Higher gene expression within the shortened TADs has been noted previously55 and may be linked to their relatively higher level of accessibility. Further analysis identified 110 genes (Supplementary Data 8) located in regions overlapped by shortened TADs and reorganized LADs or altered non-LAD lamina-chromatin binding peaks, with the highest co-enrichment to senescence/geroprotection-associated profile in normal hMSCs aging (Fig. 6k). Among them, 80 were downregulated while 30 were upregulated (FDR < 0.05) (Supplementary Fig. 16b). For example, shortened TADs of SETDB2, a H3K9me3 methyltransferase, was accompanied by lower ATAC, reduced H3K27ac and decreased transcription in MAD-MSCs (3.4-fold decrease, FDR = 5.80E-66) (Fig. 6j). Similarly, PPARα, a member of the peroxisome proliferator-activated receptor regulating energy metabolism and oxidative stress during aging process, was repressed (3.2-fold decrease, FDR = 1.18E-85) (Supplementary Fig. 16d). In addition, KRT19, a type I cytokeratin mainly expressed in epidermis and involved in mesenchymal-epithelial transition (MET), was upregulated in MAD-MSCs (6.8-fold increase, FDR = 9.15E-281), possibly linked to the changes in shortened TADs and local chromatin state(Supplementary Fig. 16d). GO term analyzes revealed the enrichment in ECM regulation, collagen biogenesis, ossification, and DNA binding transcription factor activity in MAD-MSCs (Supplementary Fig. 16c). Dysregulation of ECM remodeling and collagen biogenesis are known to be involved in aging both in vitro and in vivo56,57. Acroosteolysis is an important feature of MAD while chronic bone loss is a typical clinical manifestation in normal aging. The enrichment of negative regulation of ossification associated with TAD shortening (Supplementary Fig. 16c) was cosistent with observed acroosteolysis in MAD.
At the chromatin loop level, 5121 strengthened and 4496 weakened chromatin loops genome-wide were annotated in MAD-MSCs (Fig. 7a). Among which, 2008 and 2030 enhancer-promoter (E–P) loops were further identified based on H3K27ac signals (Fig. 7a). These differential E-P loops presented significant correlation with transcription regulation as strengthened E-P loops occupied regions of elevated gene expression (p = 1.8e − 07) while weakened E-P loops hold decreased transcription (p = 0.0026) (Fig. 7b), corresponding to 126 upregulated genes and 99 downregulated genes, respectively (Supplementary Fig. 17a; Supplementary Data 9). Intersection analyzes of the datasets revealed the highest co-enrichment in senescence-associated genes and geroprotection-associated genes between MAD-MSCs and hMSCs of normal aging (Fig. 7c). For examples, E-P loop was strengthened in TGFB2 locus with abnormal activation of TGF-β2 (29.7-fold increase, FDR = 0, n = 5) (Fig. 7d), a member of TGF-β family exhibiting inhibitory effect on cell proliferation and induces cellular senescence58. Conversely, CBX7, a geroprotection associated gene encoding a component of the polycomb group PRC1-like complex59, was decreased (4.4-fold decrease, FDR = 1.12E-84, n = 10) due to weakened E-P loop (Fig. 7d). Interestingly, E-P loop of KDM6A locus was weakened in MAD-MSCs with a decreased expression of KDM6A (2.1-fold decrease, FDR = 5.71E-40, n = 5), a demethylase of H3K27me3 (Fig. 7d). The reduced KDM6A in MAD-MSCs may explain why global loss of H3K27me3 was not observed in MAD-MSCs, contrary to the reduced H3K9me3. In addition, dysregulation of senescence-associated gene, such as MMP1460 (3.2-fold increase, FDR = 1.66E-161, n = 5), (Supplementary Fig. 17d), fell into the altered E-P loop. Additionally, several other potential aging-associated genes resulted from E-P loop alterations were also annotated, including TBX2 (5.1-fold decrease, FDR = 1.09E-226, n = 14), PCK2 (2.8-fold decrease, FDR = 1.18E-41, n = 5) and MMP16 (59.5-fold increase, FDR = 0, n = 5) (Supplementary Fig. 17d). These data indicate that mutant lamin A/C is associated with global disorganization of the chromatin hierarchy, potentially contributing to accelerated aging in stem cells by influencing the regulation of genes involved in epigenetic modification, senescence, and geroprotection.
a Statistical analysis of global changes in chromatin loop and enhancer-promoter loop. b The transcription changes of altered E-P loops in MAD-MSCs. All p-values were determined using the two-sided Wilcoxon rank-sum test. c Cross-analysis of the enrichment of dysregulated genes resulted from E-P loop alteration in MAD-MSCs with geroprotection/senescence-associated profile plotted by hMSCs aging models. Color depth indicates enrichment score. d Representative transcriptional dysregulation corresponds with strengthened and weakened E-P loops, respectively.
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- Source: https://www.nature.com/articles/s41467-024-54338-3