Foxm1 Repression During Human Aging Leads to Mitotic Decline and Aneuploidy-Driven Full Senescence

ARTICLE

DOI: 10.1038/s41467-018-05258-6 OPEN FoxM1 repression during human aging leads to mitotic decline and aneuploidy-driven full senescence

Joana Catarina Macedo1,2, Sara Vaz1,2, Bjorn Bakker3, Rui Ribeiro 1,2, Petra Lammigje Bakker3, Jose Miguel Escandell4, Miguel Godinho Ferreira 4,5, René Medema6, Floris Foijer 3 & Elsa Logarinho 1,2,7

1234567890():,; Aneuploidy, an abnormal chromosome number, has been linked to aging and age-associated diseases, but the underlying molecular mechanisms remain unknown. Here we show, through direct live-cell imaging of young, middle-aged, and old-aged primary human dermal fibroblasts, that aneuploidy increases with aging due to general dysfunction of the mitotic machinery. Increased chromosome mis-segregation in elderly mitotic cells correlates with an early senescence-associated secretory phenotype (SASP) and repression of Forkhead box M1 (FoxM1), the transcription factor that drives G2/M gene expression. FoxM1 induction in elderly and Hutchison–Gilford progeria syndrome fibroblasts prevents aneuploidy and, importantly, ameliorates cellular aging phenotypes. Moreover, we show that senescent fibroblasts isolated from elderly donors’ cultures are often aneuploid, and that aneuploidy is a key trigger into full senescence phenotypes. Based on this feedback loop between cellular aging and aneuploidy, we propose modulation of mitotic efficiency through FoxM1 as a potential strategy against aging and progeria syndromes.

1 Aging and Aneuploidy Laboratory, IBMC, Instituto de Biologia Molecular e Celular, Universidade do Porto, 4200-135 Porto, Portugal. 2 i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal. 3 European Research Institute for the Biology of Aging, University of Groningen, University Medical Center Groningen, NL-9713 AV Groningen, The Netherlands. 4 Telomere and Genome Stability Laboratory, Instituto Gulbenkian de Ciência, 2781-901 Oeiras, Portugal. 5 Telomere Shortening and Cancer Laboratory, Institute for Research on Cancer and Aging (IRCAN), UMR7284, U1081, UNS, 06107 Nice, France. 6 Division of Cell Biology and Cancer Genomics Center, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. 7 Cell Division Unit, Faculty of Medicine, Department of Experimental Biology, Universidade do Porto, 4200-319 Porto, Portugal. Correspondence and requests for materials should be addressed to E.L. (email: [email protected])

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6

umerous studies over the past decades have supported a premature cellular aging27. Considering that during a normal link between aging and aneuploidy1. This association has post-natal lifespan, cells in vivo will hardly reach the exhaustion N 28 been well documented for oocytes and is considered to be number of replications observed in culture , and to limit any the main cause of miscarriage and birth defects in humans2. artifacts and clonal selection of in vitro culturing, only early cell However, aneuploidy can also arise in somatic cells, and a culture passages (≤5) way below replicative lifespan exhaustion number of studies have reported age-dependent increases in were used (population doubling level (PDL) < 24; Supplementary aneuploidy3–7. These studies have shown that aging is positively Table 1 and Methods). Chronic accumulation of macromolecular correlated with the incidence of chromosome mis-segregation, damage during natural aging induces a cellular stress response raising the question whether there is a general dysfunction of the known as senescence29, and accumulation of senescent cells has mitotic apparatus in aged cells8. Transcriptome analyses of a been widely reported for chronological aging and age-related panel of fibroblast and lymphocyte cultures from young and old disorders30,31. Accordingly, we found higher levels of senescence- individuals revealed changes in the expression of genes control- associated (SA) biomarkers32, measured under strict quantitative ling the mitotic machinery9,10. However, the use of mixed cell parameters by microscopy analysis, in the proliferating fibroblast populations in different stages of the cell cycle and the lower cultures from older individuals and the HGPS patient (Supple- mitotic indexes (MIs) of elderly cell cultures has limited these mentary Fig.1 a–e), thus validating their suitability as models of studies from clearly demonstrating whether mitotic genes are advanced and premature aging, respectively. repressed intrinsically in old dividing cells. Moreover, analysis of To determine whether aneuploidy increases with aging, we the mitotic process in aging models and diseases has been scarce performed fluorescence in situ hybridization (FISH) for three and a comprehensive analysis of cell division efficiency in natu- chromosome pairs in asynchronous cell populations from rally aged cells is largely missing. different age donors and scored all samples blindly. We found More recently, aneuploidy has been also linked to aging. significantly higher (two-tailed χ2 test) aneusomy indices (ratio of Mutant mice with low levels of the spindle assembly checkpoint aneusomic cells for chromosomes 7, 12, and 18 to the total cell (SAC) protein BubR1 were found to develop progressive aneu- count for a sample) in the middle-aged, old-aged, and progeria ploidy along with a variety of progeroid features, including short samples (Fig. 1a). Interestingly, in these samples, not all single- lifespan, growth retardation, sarcopenia, cataracts, loss of sub- chromosome aneusomy indices were significantly higher, sug- cutaneous fat, and impaired wound healing11–14. In addition, gesting that a combination of multi-chromosome aneusomy systematic analyses of disomic yeast, trisomic mouse, and human indices is a stronger predictor of mild aneuploidy levels if there cells, all cells with an extra chromosome, have elucidated the are chromosomes with unequal probability of contributing to impact of aneuploidy in cellular fitness15. The cumulative effect of aneuploid progeny or if different aneuploidies are distinctly copy number changes of many genes induces the so called pan- selected in the cell population (Supplementary Table 2). More- aneuploidy phenotypes, namely proliferation defects16,17, gene over, as aneuploid cells are most likely outcompeted in culture by signature of environmental stress response18,19, multiple forms of diploid cells16, thereby diluting the aneuploidy index, we genomic instability20–22, and proteotoxicity23–25, which, inter- additionally measured the rate of chromosome mis-segregation estingly, are hallmarks of cellular aging26. (number of events in which two sister chromatids co-segregate to Together, these observations suggest that there is a positive the same daughter cell) by combining a cytokinesis-block assay correlation between aging and aneuploidy, but evidence for with FISH staining. In this approach, we scored all binucleated mitotic decline in elderly dividing cells and for aneuploidy-driven (BN) cells generated during a 24 h treatment with cytochalasin D permanent loss of proliferation capacity (full senescence) is lim- (cytokinesis inhibitor; see Methods). We found the percentage of ited. Here, we used live-cell time-lapse imaging to investigate the BN cells with chromosome mis-segregation over the total BN cell mitotic behavior of human dermal fibroblasts (HDFs) collected count for a sample to be significantly higher (two-tailed χ2test) in from healthy Caucasian males with ages ranging from neonatal to the middle-aged, old-aged, and progeria cultures (Fig. 1b). Taken octogenarian and cultured under low passage number. We show together, these FISH experiments show that increased mis- that mitotic duration increases with advancing age, concurrent segregation rates are associated with mild aneuploidy levels in with a higher rate of mitotic defects. We demonstrate this mitotic elder cultures, supporting the idea of an age-associated loss of decline to arise from a transcriptional repression of mitotic genes mitotic fidelity. in pre-senescent dividing cells exhibiting senescence-associated secretory phenotype (SASP). We show short-term induction of Forkhead box M1 (FoxM1) transcriptional activity to improve Elder cells divide slower with increased rate of mitotic defects. mitotic fitness and ameliorate senescence phenotypes in elderly To gain insight into how old cells divide, we followed individual and progeroid cells. Finally, we show aneuploidy to induce full mitotic cells by long-term phase-contrast time-lapse imaging. senescence in naturally aged cells, which suggests that mitotic Interestingly, we found the interval between nuclear envelope fitness enhancement may be a potential anti-aging strategy. breakdown (NEB) and anaphase onset to increase steadily with advancing age (Fig. 1c, d). To exclude any effects due to genetic heterogeneity between the Caucasian donors and/or biobank Results discrepancies in culture set up, we used mouse adult fibroblasts Aneuploidy increases during natural aging. In our study, we recurrently sampled from female mice over a period of 2 years. In used HDFs collected from healthy Caucasian males with ages this model, culture conditions were highly homogenous, thereby ranging from neonatal to octogenarian (Supplementary Table 1), providing a solid “ex vivo” model of chronological aging. Again, to test whether aneuploidy increases during natural aging and if both mitotic duration (Supplementary Fig. 2a–c) and SA bio- this is a consequence of a general dysfunction of the mitotic markers (Supplementary Fig. 2d, e) progressively increased with machinery in aged cells. As inter-individual differences exist in aging. the rate at which a person ages (biological age), we included two We then asked what could be leading to the age-associated donors of each age in a total of five chronological ages to increase mitotic delay. Bypass of short telomere-triggered senescence by the robustness of any correlation found with aging. In addition, disruption of tumor-suppressive pathways, shown to elicit we used dermal fibroblasts from an 8-year-old child with the telomere fusion-driven prolonged mitosis33, was ruled out as Hutchison–Gilford progeria syndrome (HGPS) as a model of potential cause, as we found no evidence for chromosome fusions

2 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

ab Interphase FISH 4 Cyto D FISH 4

2N 2N

3 3 *** * 2N

2 *** 2 * n.s. p=0.061 2N+1 * 2N+1

1 1 = 904 = 481 = 502 = 396 = 457 = 204 n n n n n n

2N-1 BN cells with mis-segregation (%) = 4064 = 5117 = 3120 = 2578 = 6178 = 3141 Aneusomy index of Chr 7+12+18 (%) n n 0 n n n n 0 chr 7 chr 12 chr 18 chr 7 chr 12 chr 18 N/N N/N 8/10y Prog 8/10y Prog 22/22y 52/54y 84/87y 22/22y 52/54y 84/87y c NEB ANA HDF N

–5:00 0:00 20:00 22:30 25:00 52:30

NEB ANA HDF 87y

–5:00 0:00 27:30 30:00 32:30 45:00

NEB

HDF 87y + Mps1 i –5:00 0:00 10:0012:30 15:00 32:30

de 100 **** 40 **** **** Untreated **** **** + Mps1 i 80 **** 30 **** **** **** **** 60 *** **** 20

20 NEB-anaphase onset (min) NEB-anaphase onset (min) = 164 =49 = 219 =65 = 192 = 145 = 147 =58 = 143 = 138 = 123 =71

n = 251 n = 364 n = 365 n = 429 n = 371 n = 194 n n n n n n n n n n n n 0 0

N/N N/N 8/10y Prog 8/10y Prog 52/54y 84/87y 22/22y 52/54y 84/87y 22/22y

Fig. 1 Aneuploidy and mitotic duration increase during normative aging. a Aneusomy index of three chromosome pairs (7, 12, and 18) in interphase cells from different age donors. b Percentage of cytochalasin D-induced binucleated cells with chromosome 7, 12, and 18 mis-segregation. Representative images of euploid/2N and aneuploid/2N ± l cells are shown in a, b, with chromosome-speciﬁc centromeric probes as indicated. Scale bars, 5 µm. c Frame series of time-lapse phase-contrast movies of mitotic neonatal and elderly cells ± Mps1 inhibitor. Time, min:s. Scale bar, 20 µm. d Mitotic duration of individual ﬁbroblasts from different donors, measured from nuclear envelope breakdown (NEB) to anaphase onset (ANA). e Mitotic duration under standard conditions as in d (white bars) and following treatment with Mps1 inhibitor (gray bars). Values are mean ± SD from at least three independent experiments, using two biological samples of similar age (except for progeria). Sample size (n) is indicated in each graph. NS, p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 in comparison with neonatal (N/N) by two-tailed χ2 (a, b) and Mann–Whitney (d, e) statistical tests

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 3 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 in metaphase spreads of the primary dermal fibroblasts used in neonatal mitotic fibroblasts (Fig. 3d; Supplementary Data 1). our study (Supplementary Fig. 3a). Activation of the SAC by Principal component analysis showed that two independent defective kinetochore–microtubule attachments and/or reduced experiments from the same donor were consistent for the main efficiency of the ubiquitin-proteasome system induced by component (Fig. 3e). In agreement with the elderly cell defects in proteotoxic stress could alternatively explain the delay between mitosis, the top 10 most altered Gene Ontology (GO) terms NEB and anaphase onset in older cells. We found the mitotic included six cell cycle-related and mitosis-related gene ontologies delay to depend on SAC activity as treatment with a small (Fig. 3f). Seventy-one “mitosis” GO genes were altered in molecule inhibitor of the Mps1 kinase rescued mitotic duration to octogenarian mitotic fibroblasts (p-value < 0.05; likelihood ratio similar levels in all cell cultures (Fig. 1c, e). Enhancement of test; Supplementary Data 2), representing a 1.97-fold enrichment proteasome activity with a small molecule inhibitor of the Usp14 of alterations in this gene set (p-value = 9.73E−9, Fisher deubiquitinase did not change mitotic duration considerably exact test) (Fig. 3g). Moreover, a comprehensive list of 51 SA (Supplementary Fig. 3b). As a correlation between cell size, genes, including CDKN1A, CDKN2A, GLB1, LMNB1, and SASP mitotic duration, and SAC strength was recently described34,we genes (i.e., chemokines, cytokines, metalloproteinases, and others) further tested whether aging-associated mitotic delay was due to 36,37, was interrogated in the RNA-seq data set (Supplementary increased cell size. We found no correlation between mitotic Data 3). We found altered expression of 26 genes in the elderly vs. duration and cell size in fibroblast cultures (Supplementary Fig. 3 neonatal mitotic cells, with 19 genes behaving as previously c-f). In addition, when treated with taxol and the kinesin-5 reported36,37 (Fig. 3h; Supplementary Data 4). As the transcrip- inhibitor (S-Trityl-l-cysteine, STLC) to induce chronic activation tome of senescent cells is highly heterogeneous and depends on of the SAC, elderly cells arrested in mitosis as long as young cells the cell type and senescence stimulus, we additionally extended before they slipped out, suggesting that SAC strength is similar our analysis into 55 genes recently identified as comprising a (Supplementary Fig. 3g, h). “senescence core signature37.” Indeed, we found 19 genes of this To investigate chromosome and/or spindle defects contributing signature to be differentially regulated in the RNA-seq data set of to increased mitotic duration in older cells, we performed high- mitotic octogenarian dermal fibroblasts, with 16 genes behaving resolution spinning-disk confocal microscopy in cells expressing as reported37 (Fig. 3i; Supplementary Data 5). Alterations in the H2B–GFP and α-Tubulin–mCherry (Supplementary Movies 1– expression levels of CDKN1A, MMP1, CXCL8, TSPAN13, and 4). We found several mitotic defects to be increased in middle- FAM214B, were further confirmed by real-time PCR analysis aged and old-aged samples (Fig. 2a–f), namely chromosome (Fig. 3j). Thus, an unforeseen SASP phenotype evolves in elderly congression delay (Fig. 2b, e, f; Supplementary Movie 2), dividing cells, alongside a global transcriptional shutdown of anaphase lagging chromosomes (Fig. 2c, e, f; Supplementary mitotic genes, likely accounting for aging-associated mild Movie 3), and spindle mispositioning in relation to the growth aneuploidy levels. surface (Fig. 2d–f; Supplementary Movie 4). In agreement with proper SAC functioning (Supplementary Fig. 3g, h), aged cells entering anaphase with unaligned chromosomes were never FoxM1 repression dictates mitotic decline during natural observed. Moreover, we found middle-aged, old-aged, and HGPS aging. RNA-seq analysis also disclosed FOXM1, the transcription cells to more often exhibit micronuclei (an outcome of anaphase factor that primarily drives the expression of G2/M cell cycle lagging chromosomes35; Fig. 2g) and fail cytokinesis (Fig. 2h), genes38,39 (Fig. 4a), to be downregulated in elderly mitotic cells based on complementary quantitative cell-based assays (fixed-cell (2logFC: −0.85; false discovery rate (FDR) < 5%; likelihood ratio analysis and phase-contrast live-cell imaging, respectively; test; Supplementary Data 1). Indeed, 36 out of the 71 mitotic Methods). Overall, the data indicated that aging triggers genes altered in octogenarian mitotic cells have been reported as abnormalities at several mitotic stages, in agreement with the targets of the Myb-MuvB (MMB)-FOXM1 transcription complex increased levels of aneuploidy found. containing the cell cycle genes homology region (CHR) motif in their promoters38–40 (Fig. 3b; Supplementary Data 6). In addition, loss of FOXM1 has previously been shown to cause pleio- Mitotic gene transcriptional shutdown and SASP in elderly tropic cell cycle defects leading to embryonic lethality41.We mitotic cells. To identify the molecular mechanisms behind this therefore asked whether loss of mitotic proficiency during nor- complex aging-associated mitotic phenotype, we performed mative aging was due to FOXM1 downregulation. Indeed, RNA-sequencing (RNA-seq) gene expression profiling of cells increasing age correlated with decreased FoxM1 transcript and captured in mitosis, accordingly to the experimental layout shown protein levels in our human (Fig. 4c–e) and mouse (Supple- in Fig. 3a. Fibroblast cultures from neonatal and octogenarian mentary Fig. 2f–h) mitotic cell samples. Importantly, unlike donors were treated with STLC to enrich for MI, and mitotic cells previous studies linking FoxM1 repression and aging42,43,by collected by mechanical detachment. As cell synchronization analyzing mitotic cell samples, we uncoupled FoxM1 down- (mitotic enrichment) was limited in elderly vs. neonatal cultures, regulation from decreased cell proliferative capacity, demon- we used a higher number of cell culture flasks with octogenarian strating that elderly cells divide with intrinsically low levels of fibroblasts treated with STLC to collect equivalent numbers of FoxM1. To get evidence that FoxM1 repression actually accounts mitotic elderly and neonatal cells for RNA-seq. The procedure for an elderly cell mitosis with low mitotic protein levels, we yielded purified cell populations with mitotic indices >95% in measured the protein levels of FoxM1 and some of its known both neonatal and 87 y donor cultures (Fig. 3b, c), and impor- mitotic targets (Cyclin B1, Plk1, Ndc80, and Cdc20)44 by western tantly, it uncoupled any changes found in mitotic gene expression blotting analysis of mitotic cell extracts (Fig. 4f, g), as well as by from the samples’ differences in MI (Supplementary Fig. 4a) and immunofluorescence analysis of single mitotic cells (Fig. 4h–j; overall proliferation capacity (Supplementary Table 1). Moreover, Supplementary Fig. 5). These quantitative analyses demonstrated apoptosis was excluded as potential cause of reduced proliferation that in elderly mitotic cells, important protein players acting from in elderly cell samples as similar levels of apoptotic cells were mitotic entry (e.g., Cyclin B1) to anaphase onset (e.g., Cdc20) are found in neonatal and octogenarian samples by flow cytometry in fact expressed at low levels. We thus conclude that an aging- analysis for annexin V staining (Supplementary Fig. 4b, c). associated FoxM1 repression likely accounts for an extensive RNA-seq revealed that the abundance of 3309 gene transcripts transcriptional downregulation of mitotic genes and the pheno- was altered in octogenarian mitotic fibroblasts compared to types observed in early senescent dividing cells.

4 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

a NEB ANA HDF N

0:00 6:00 13:30 19:30 22:30 36:00

b NEB ANA Chromosome misalignment HDF 87y

Chromosome misalignment 0:00 18:00 22:3025:30 30:00 51:00

c NEB ANA

Anaphase lagging * * HDF 87y

0:00 18:00 22:30 25:30 27:00 34:30

d NEB ANA

HDF 87y Spindle Spindle mispositioning mispositioning Asynchronous 0:00 16:30 25:30 60:00adherence 70:30 76:30

efLagging chromosome + spindle mispositioning g h Mitotic phenotypes (%) 4 Chr alignment delay + spindle mispositioning 6 100 100 Lagging chromosome **** **** Chr alignment delay ns Spindle mispositioning p = 0.09 80 Normal 80 3 *** * 4

ns 60 60 * ** * 2

40 40 * Micronuclei (%) 2

1 Cytokinesis failure (%)

NEB-anaphaseonset (min) 20 20 = 1636 = 1505 = 1784 = 1247 = 2032 = 1617 =334 =477 =359 =324 =239 =390

n =25 n =15 n =19 n =19 n =40 n =6 n n n n n n n n n n n 0 0 0 0 n

N/N 8/10y Prog N/N Prog N/N Prog N/N 8/10y Prog 22/22y 52/54y 84/87y 8/10y22/22y 52/54y 84/87y 8/10y 22/22y 52/54y 84/87y 22/22y52/54y84/87y

Fig. 2 Mitotic defects associated with advanced age. a–d Frame series of spinning-disk confocal movies of neonatal (HDF N) and elderly (HDF 87 y) dividing cells expressing H2B–GFP/α-Tubulin–mCherry. a Neonatal cell division. b–d Elderly cell with chromosome alignment delay (b) with anaphase lagging chromosome and micronucleus formation (*) (c) or with spindle mispositioning in relation to the growth surface and asynchronous adherence of the daughter cells (d) (Supplementary Movies 1–4). Time, min:s. Scale bar, 5 µm. e Mitotic duration (NEB to anaphase onset) of HDFs from different age donors imaged under spinning-disk confocal microscopy. Mitotic phenotypes are indicated by distinct colors. f Quantiﬁcation of the observed mitotic phenotypes. g Percentage of cells with micronuclei in ﬁxed-cell analysis. h Rate of cytokinesis failure under phase-contrast microscopy. Values are mean ± SD from at least two independent experiments, using two biological samples of similar age (except for progeria). Sample size (n) is indicated in each graph. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 in comparison with N/N by two-tailed Mann–Whitney (e) and χ2 (g, h) statistical tests

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To test the correlation between FoxM1 repression and age- enriched for mitosis genes (143 genes, GO analysis; FDR < 5%, associated phenotypes further, we RNA interference (RNAi)- likelihood ratio test) (Fig. 5a; Supplementary Data 8). This depleted FoxM1 in ﬁbroblasts from the 10-year-old donor constituted a 2.41-fold enrichment of alterations in this gene set (Supplementary Fig. 6a). Again, to uncouple gene expression (p-value = 7.43E−32, Fisher exact test). The top ten most altered analysis from the reduction in MI following FoxM1 RNAi GO terms included six related to mitosis (Supplementary Fig. 8d), (Supplementary Fig. 6b), we performed RNA-seq proﬁling of cells and 224 out of 249 G2/M cell cycle genes previously reported as captured in mitosis accordingly to the experimental layout in targets of the DREAM (DP, RB-like, E2F4, and MuvB) and Fig. 3a (Supplementary Fig. 6c). RNA-seq revealed that FoxM1 MMB-FOXM1 transcriptional complexes39, were downregulated repression altered the abundance of 5841 gene transcripts following FoxM1 depletion (Supplementary Fig. 8d). Moreover, (Supplementary Fig. 8a,b; Supplementary Data 7), which were we found 1937 out of the 3309 genes altered in old-aged

abHDF N HDF 87y 1

Protein extract WB Collect mitoses (shake off) qRT-PCR Total RNA RNA seq 1 2 STLC 16 h Score MI Purity and integrity validation 2

c ns dfHDF N vs 87y e 100 2000 HDF N vs 87y altered genes Neo_1 1.5 Top 10 GO terms p value 80 1.0 87y_1 Cell cycle 1.3E–14 1500 Skeletal system development 1.8E–13 60 0.5 Cell cycle process 2.3E–12 0.0 Cell division 4.5E–09 1000 Cell cycle phase 4.6E–09 40 –0.5 Skeletal system morphogenesis 5.2E–09 Mitotic cell cycle 6.7E–09 Mitotic index (%)

500 Leading logFC dim 2 –1.0 20 7.4E–09 No of altered genes Neo_2 Regulation of cell death –1.5 87y_2 Regulation of programmed cell death 9.1E–09 1436 1873 Mitosis 9.7E–09 0 0 −2 −1 0 1 2 Neo 87y Up Down Leading logFC dim 1

g Significantly different among ‘mitosis’ genes

1 1 0.5

HDF N 2 0

1 –0.5 2 –1 HDF 87y Column CIT

PBK Z score OIP5 PLK1 TPX2 FSD1 SKA3 PES1 NUF2 BUB1 EML4 NEK2 NEK3 NEK6 CDK1 ANLN CDK2 NDE1 KIF22 KIF15 KIF23 RCC1 SGO1 Gene BORA KIF2C BIRC5 ESPL1 symbol CEP55 HELLS SPC24 PTTG1 NUP37 CDC20 NDC80 KNTC1 LRCC1 STAG2 BUB1B PAPD5 RGS14 FBXO5 HAUS4 HAUS8 SUGT1 KIF18A SPAG5 CCNA2 CDCA5 CDCA8 CCNB1 CCNB2 CDCA2 AURKA CENPV CCNG2 VCPIP1 ZNF830 ZC3HC1 MAD2L1 KATNA1 MAD2L2 RUVBL1 CDC25A ERCC6L DLGAP5 CDC25C NCAPD2 MAPRE1 NCAPG2 MAPRE2 CHMP1A 1.3474 1.4399 1.2900 1.4920 0.5274 0.5334 0.7492 1.1413 0.7217 2.1001 0.9989 2logFC –0.9206 –0.8594 –1.1436 –0.7568 –0.7702 –0.7328 –0.9872 –0.6580 –1.0769 –0.9731 –0.7172 –0.5848 –0.9072 –0.6864 –1.1825 –0.6552 –0.9459 –0.6882 –0.9512 –0.5681 –0.5129 –1.5701 –1.0352 –1.0574 –1.4399 –1.4768 –1.6549 –1.1138 –0.5537 –2.4317 –0.5642 –1.1750 –0.6227 –4.0222 –0.6979 –0.6709 –1.2173 –1.0521 –0.8061 –1.0308 –1.0637 –1.3463 –0.5494 –0.8216 –0.6178 –0.9591 –0.9325 –0.6173 –0.8672 –0.8226 –0.9141 –0.5396 –0.9178 –0.5725 –0.6013 –0.8941 –0.7281 –1.2996 –0.7385 –1.4580

h ijSenescence core signature genes SASP genes Down Up 20 1 1 −1 −1 * −0.5 −0.5 15 HDF N 2 HDF N 2 0 0 1 0.5 1 0.5 10 1 1 p =0.08 2 2 ** HDF 87y Column HDF 87y Column 5 * ** Z score Z score Gene/ TBP mRNA SMO PLK3 FGF7 CCL2 FGF2 MST1 BDNF BMP6 GBE1 Gene UFM1 RAI14 MMP1 MMP3 GDNF SPIN4 Gene ICAM1 MEIS1 TAF13 symbol CXCL2 CXCL6 CXCL1 CXCL3 ZC3H4 P4HA2 LMNB1 VEGFA MMP12 MMP10 CCND1 symbol IGFBP7 IGFBP4 IGFBP2 RHNO1 DYNLT3 PLXNA3

CDKN1A 0 SLC16A3 TSPAN13 FAM214B TMEM87B TNFRSF1B CXCL8 (IL8) TNFRSF11B TNFRSF10D TNFRSF10C Neo Neo Neo Neo Neo 84/87y 84/87y 84/87y 84/87y 84/87y 0.9464 1.1979 0.5113 0.6105 1.3657 0.7024 1.4413 0.9767 0.8735 0.8024 0.6380 3.1853 2.2459 0.8144 2logFC –1.1277 –0.7392 –0.9910 –1.9242 –1.1812 1.3754 3.9859 0.9981 1.5706 1.3405 2.1310 1.1939 2.5423 1.4633 1.9319 4.5492 2.9901 1.6545 3.1795 1.2330 1.0149 1.5253 2.2254 −0.921 2logFC −3.2951 −1.3039 −1.1927 −1.9695 −0.7617 −5.2338 −4.0622 MMP1 TSPAN13 FAM214B CXCL8 (IL8) CDKN1A (p21)

6 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

fibroblasts, to be also altered in FoxM1-depleted cells (Fig. 5b; only mild overexpression of FoxM1-dKdK is sufficient to over- Supplementary Data 9). Thus, 58.5% of the age-dependent come the aging phenotypes (Supplementary Fig. 7j, k). To gain transcriptional changes are FoxM1-dependent and enriched for insight into the SA genes found altered in elderly cells that rely on cell cycle/mitosis GO terms (Fig. 5b). In agreement, FoxM1- FoxM1 expression levels, we compared the senescence response depleted young fibroblasts displayed decreased protein levels of between 87 y FoxM1-dNdK and 10 y siFoxM1 samples (Supple- FoxM1 targets (Supplementary Fig. 6d, e), a mitotic delay (Fig. 5c), mentary Fig. 8e, f). We found that both SASP and senescence core mitotic defects (Supplementary Fig. 6f–h), and increased aneuploidy signature genes are largely regulated by FoxM1 levels, with 19 (Fig. 5d, e), similar to old-aged fibroblasts. Interestingly, the SASP genes and 14 senescence core signature genes consistently percentage of cells with SA biomarkers also increased following altered in all experimental conditions. Further validating our FoxM1 repression (Fig. 5f, g), further supported by changes in the experimental conditions of FoxM1 expression modulation, we expression levels of SASP genes and genes of the senescence core found extensive overlap between genes altered in 10 y siFoxM1 signature (Fig. 5h, i; Supplementary Fig. 6i; Supplementary Data 10; and 87 y FoxM1-dNdK (1915 genes; Supplementary Fig. 8d; Supplementary Data 11). Altogether, these results show that young Supplementary Data 17), with 158 out of the 249 DREAM/MMB- cells with low levels of FoxM1, equivalent to those in octogenarian FOXM1 gene targets included in this overlap. Importantly, cells (Supplementary Fig. 7j,k), recapitulate the aging-associated FoxM1-dNdK expression also partly rescued the mitotic defects mitotic defects, aneuploidy, and senescence phenotypes. (Supplementary Fig. 9a–d; Supplementary Movies 7, 8), aneuploidy levels (Supplementary Fig. 9e, f), and percentage of senescent cells (Supplementary Fig. 9g, h) in HGPS fibroblasts. FoxM1 induction rescues aging phenotypes in elderly and Overall, these data demonstrate that modulation of mitotic effi- HGPS cells. As FoxM1 depletion reduced mitotic fidelity and ciency through FoxM1 induction in elderly and HGPS cells induced senescence in young cells, we hypothesized that FoxM1 prevents aneuploidy and delays cellular senescence. overexpression in elderly cells should counteract aging phenotypes. Expression of a constitutively active truncated form of FoxM1 (FoxM1-dNdK) in old-aged fibroblasts45,46 (Supplemen- Increased aneuploidy in elderly senescent cells. Experimental tary Fig. 7a) increased MI (Supplementary Fig. 7b) and resulted in modulation of FoxM1 levels in the young (FoxM1 RNAi) and altered expression of 2966 gene transcripts as determined by elderly fibroblasts (FoxM1-dNdK) demonstrated an inherent link RNA-seq profiling of cells captured in mitosis accordingly to between aneuploidy and senescence. Previous studies have found experimental layout in Fig. 3a (Supplementary Fig. 7c; Supple- cellular/mouse models of constitutional aneuploidy or chromo- mentary Data 12; Supplementary Fig. 8a, c). Altered gene tran- somal instability (CIN) to prematurely senesce/age11,47–51. scripts were enriched for “mitosis” GO genes (79 genes; Fig. 6b; Although informative, these studies either represent conditions Supplementary Data 13). To gain insight into the mitosis genes where aneuploidy is present from early development onward and/ found altered in elderly cells that are dependent on FoxM1 or conditions where CIN-inducing single gene editing/drug transcriptional activity, we performed comparative analysis with treatment leads to higher aneuploidy levels than those accumu- mitosis genes altered in 87 y FoxM1-dNdK and 10 y lated during normal aging. Whether the mild aneuploidy levels siFoxM1 samples (Fig. 6c; Supplementary Data 14). Fifty genes caused by global transcriptional shutdown of mitotic genes out of the 71 mitosis genes altered in 87 y cells were also altered in account for cellular senescence in natural aging remains FoxM1-dNdK and siFoxM1 experimental conditions, suggesting unknown. To address this question, we fluorescence-activated that FoxM1 primarily accounts for age-related mitotic pheno- cell (FACS)-sorted senescent cells from neonatal and elderly types. Concordantly, mitotic protein levels (Supplementary fibroblast cultures using SA-β-galactosidase (SA-β-gal) as a Fig. 7d, e) and age-associated mitotic defects were ameliorated in senescence marker and measured the aneusomy index of three elderly fibroblasts expressing FoxM1-dNdK (Fig. 6a, d; Supple- chromosome pairs (Fig. 6a–f). As expected, the percentage of SA- mentary Movies 5, 6; Supplementary Fig. 7f–h), resulting in β-gal-positive cells was considerably higher in elderly vs. neonatal decreased aneuploidy levels (Fig. 6e, f). Furthermore, the per- early passage cell cultures (Fig. 7a, b, e), and consistent with our centage of cells with SA biomarkers was decreased (Fig. 6g, h), quantitative analysis using fluorescence microscopy (Supple- consistently to amelioration of SASP and senescence core tran- mentary Fig. 1a). Strikingly, even though the aneusomy indices of scriptional signatures (Fig. 6i, j; Supplementary Fig. 7i; Supple- SA-β-gal-positive cells were significantly higher (two-tailed χ2 mentary Data 15; Supplementary Data 16). Interestingly, the test) than those of unsorted controls in both neonatal and elderly aging phenotypes were rescued by restoring FoxM1 levels in samples, we found a cumulative 9.1% aneusomy index for three elderly cells to the levels as present in young cells, indicating that assessed chromosome pairs in elderly senescent cells in

Fig. 3 Mitotic gene downregulation and senescence gene signature in elderly mitotic fibroblasts. a Experimental layout. Fibroblast cultures from different age donors were treated with kinesin-5 inhibitor (STLC) to enrich for mitotic index (MI). Mitotic (detached) cells were collected and inspected for MI. Protein extracts and total RNA were prepared for gene expression analyses. b Representative images of neonatal (HDF N) and elderly (HDF 87 y) mitotic cell shake-offs. Insets are ×2 magnifications. Scale bar, 50 µm. c MI quantification of neonatal and octogenarian mitotic cell shake-offs. d Number of altered genes in HDF 87 y RNA-seq comparing to HDF N (Supplementary Data 1). e RNA-seq multidimensional scaling (MDS) plot. Axes in MDS plot represent leading log-fold changes (logFCs) calculated by the root-mean-square of the largest absolute logFCs between each pair of libraries. f Top ten altered GO terms organized by p-values using the DAVID Functional Annotation tool. g Heatmap of genes within the “mitosis” GO term differentially expressed between HDF N and HDF 87 y (Supplementary Data 2). h Heatmap of SASP and senescence-associated (CDKN1A, LMNB1) genes differentially expressed between HDF N and HDF 87 y (Supplementary Data 4); 2logFCs in red indicate genes behaving differently from expected36, 37. i Heatmap of senescence core signature genes differentially expressed between HDF N and HDF 87 y (Supplementary Data 5); 2logFCs in red indicate genes behaving differently from expected37. In all heatmaps, 2logFC cutoff value < −0.5 and >0.5, p-value < 0.05; genes represented in columns and technical replicates represented in rows; Z-score column color intensities representing higher (red) to lower (blue) expression. j Transcript levels of senescence genes in total RNA from mitotic elderly samples normalized to TBP transcript levels and compared with neonatal. NS, p > 0.05, *p ≤ 0.05, and **p ≤ 0.01 by two-tailed Mann–Whitney statistical test (c, j)

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 7 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6

a b DREAM complex MMB-FoxM1 87y DREAM / FoxM1-MMB B-MYB “mitosis” genes targets (249) G2/M genes G2/M genes (71) p130/p107 MuvB FoxM1 MuvB OFF ON 35 36 213 DP E2F4

CDE CHR CDE CHR

cde1.2 1.2 (p = 0.067) MW ns N 10y 22y 52y 87y Prog 1.0 1.0 (kDa) *** *** 0.8 * ** 100 0.8 *** FoxM1 0.6 ** 0.6 ***

66 0.4 0.4 *** Tubulin FoxM1/tubulin

FoxM1 0.2 FOXM1/TBP mRNA 0.2 levels: 100% 84% 30% 14% 17% 30% 0 0

N/N 8/10y Prog N/N 22/22y52/54y84/87y 8/10y 22/22y 52/54y84/87y

f g hi j HDFs N/N MW 84/87y 2.0 (kDa) Neo 87y 1.5 2.0 *** 2.0 ** **** 100 FoxM1 *** ** ** **** 1.5 1.5 1.5 70 Ndc80 1.0 70 Plk1 1.0 1.0 1.0 55 CycB1 0.5 Protein/tubulin 0.5 0.5 0.5 Tubulin CycB intensity levels (A.U.) Cdc20 intensity levels (A.U.) FoxM1 intensity levels (A.U.) n =15 n =14 n =19 n =15 n =21 n =15 0 0 0 0 FoxM1 CycB1 Plk1 Ndc80 N/N N/N N/N 84/87y 84/87y 84/87y

Fig. 4 Aging cells express low levels of FoxM1 and mitotic transcripts during mitosis. a Regulation of G2/M cell cycle genes by competitive binding of DREAM and FoxM1-MMB transcriptional complexes to CDE/CHR promoter elements, as described in ref. 40. b Venn diagram displaying the overlap between mitosis genes altered in elderly fibroblasts (87 y) and targets of DREAM/FoxM1-MMB complex40 (Supplementary Data 6). c, d FoxM1 protein levels in mitotic extracts of different age samples. FoxM1 levels were normalized to α-tubulin levels and to the neonatal sample (N/N). e FOXM1 transcript levels in mitotic total RNA from different age samples normalized to TBP transcript levels and compared to neonatal. f, g Protein levels of FoxM1 transcriptional targets in mitotic extracts of neonatal and elderly fibroblasts. Values are normalized to α-tubulin levels and to the neonatal sample (N/N). h–j Quantitative analysis of FoxM1 (h), Cyclin B (i), and Cdc20 (j) immunofluorescence intensity levels in n = single mitotic cells (N/N and 84/87 y) (Supplementary Fig. 5). Relative intensity levels are indicated as arbitrary units (A.U.). Values are mean ± SD of two (h–j) or three (d, e, g) independent experiments. NS, p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 in comparison with N/N by two-tailed Mann–Whitney test comparison with 3.2% in neonatal senescent cells (Fig. 7f). Thus, cell fate of mitotic cells with chromosome segregation defects aneuploidy appears as an overt feature in elderly senescent cells, (anaphase lagging chromosome and/or micronucleus generation), especially if we consider that only 3 out of 23 chromosome pairs as well as of mitotic cells without apparent chromosome mis- were measured. To investigate whether FoxM1 repression is segregation, was tracked individually during 2–3 days for cell responsible for this difference, we next FACS-sorted SA-β-gal- death, cell cycling or senescence (SA-β-gal assay at the end of the positive cells from siFoxM1-depleted neonatal cell cultures and movie and immunostaining for 53BP1/p21) (Methods). Using from octogenarian cell cultures expressing FoxM1-dNdK this live-cell fixed-cell correlative microscopy analysis, we found (Fig. 7c–e). We observed FoxM1 repression to induce an that daughter cells from apparently normal mitoses most often increase in the percentage of SA-β-gal-positive cells and their kept on cycling (71.7 ± 0.4%; Fig. 7h, i; Supplementary Movie 9) aneusomy index, and FoxM1-dNdK expression to decrease the and cell death was never observed. Among the 28.3 ± 0.4% percentage of SA-β-gal-positive cells and their aneusomy index. daughter cells from apparently normal mitoses that stopped These results demonstrate that FoxM1 levels modulate the cycling, < 25% exhibited SA biomarkers (β-gal + or 53BP1 accumulation of aneuploid senescent cells. + /p21 + ) (Fig. 7h, i; Supplementary Movie 10). In contrast, daughter cells from mitoses with mis-segregation events consistently stopped proliferating (100%; Fig. 7h, i). Moreover, when Aneuploidy triggers full senescence following old cell division. stained for SA-β-gal and 53BP1/p21 SA biomarkers, aneuploid To directly demonstrate that aneuploidy acts as ultimate trigger daughter cells were significantly positive (46.4 ± 3.6%, p < 0.05 to elderly cell permanent cycle arrest, and thus the establishment and 85.7 ± 7.1%, p < 0.0001, respectively; two-tailed χ2 test) in of a full senescent state, we performed the experimental layout comparison with non-cycling daughter cells produced by appar- shown in Fig. 7g. Octogenarian fibroblasts expressing H2B–GFP ently normal mitoses (Fig. 7h, i; Supplementary Movie 11). were followed under long-term time-lapse microscopy. Daughter Furthermore, other senescence markers (epigenetic histone

8 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

a Significantly different among ‘mitosis’ genes

1 1 10y siCtr 0.5 2 0

1 –0.5

10y –1

siFoxM1 2

Column CIT PBK HGF RAN OIP5 PLK1 TPX2 TIPIN FSD1 PES1 SKA1 SKA2 SKA3 RNF8 NUF2 BUB1 BUB3 EML4 NEK2 NEK6 ANLN TUBB PMF1 LMLN NDE1 CDK1 CDK2 ZW10 RRS1 KIF11 KIF15 KIF22 KIF23 RCC1 CDC6 RCC2 MAP9 CCNF SMC2 MAU2 SMC4 SGO1 CCNK BORA ASPM WEE1 SIRT2 KIF2C Z score NUDC NIPBL BIRC5 LZTS2 Gene ESPL1 ZWINT SPC24 SPC25 CEP55 USP16 SEH1L SPDL1 HELLS PTTG1 NUP37 NUP43 RAD21 DDX11 AKAP8 KNTC1 CDC20 CDC23 NDC80 CDC27 CETN3 BUB1B RGS14 PDS5B FBXO5 CKAP5 PAPD7 PDS5A KMT5A HAUS7 UBE2C HAUS6 HAUS8 KIF18A KIF20B SPAG5 CCNA2 CDCA5 CCNB1 CCNB2 CENPF CDCA2 CDCA3 CDCA8 DSCC1 NEDD1 NEDD9 AURKB CENPV AURKA SMC1A CENPE PBRM1 CCNG2 CCNG1 NCAPH symbol HMGA2 NCAPG MIS18A ZNF830 CEP164 INCENP TXNL4B ZWILCH ZC3HC1 KATNA1 MAD2L1 MAD2L2 SAC3D1 ERCC6L FAM83D CDC25A CDC25B DLGAP5 CDC25C LRRCC1 ANAPC7 ANAPC1 NUSAP1 PKMYT1 NCAPD2 NCAPD3 TARDBP MAPRE1 MAPRE2 MAPRE3 NCAPG2 ANAPC13 ANAPC10 MIS18BP1 TIMELESS 0.6293 2.2144 0.6649 0.8722 0.7166 0.8048 0.5784 0.8019 0.8448 0.5750 1.2331 0.5884 1.3445 0.7673 0.8306 –2.848 –1.6449 –1.7251 –1.1540 –1.5463 –0.7065 –2.5192 –2.2106 –2.4898 –2.6609 –2.0433 –2.6324 –2.6643 –0.8735 –1.9448 –0.9374 –2.3293 –1.4011 –0.7355 –0.7371 –1.9058 –1.6294 –1.6046 –1.2413 –2.2081 –1.9422 –1.7039 –2.2982 –2.2652 –0.9604 –3.5652 –0.5807 –0.5393 –2.9786 –1.3125 –0.7952 –1.4708 –2.6251 –1.2003 –2.6490 –0.7927 –0.5660 –0.9394 –0.5294 –1.7722 –2.8513 –0.5889 –2.6207 –1.7739 –1.0122 –1.3259 –1.0275 –0.9849 –0.9081 –0.5246 –0.6917 –3.1393 –2.2285 –1.3959 –2.3973 –0.6392 –1.5103 –1.8915 –2.2580 –2.3418 –2.2996 –2.5056 –0.9815 –1.3065 –0.9760 –2.5710 –0.8965 –0.5338 –1.5748 –0.5969 –0.8176 –0.8325 –0.9735 –1.7671 –2.0751 –0.6043 –1.0761 –0.5632 –1.0770 –2.2316 –3.3353 –2.6914 –1.9852 –2.8991 –3.3132 –2.3004 –2.5066 –0.9072 –3.5137 –3.6627 –3.1094 –2.6084 –0.7476 –1.0261 –2.9208 –0.6238 –1.8933 –1.0123 –1.9703 –1.0495 –0.9240 –2.5054 –2.2416 –2.1301 –2.6091 –2.4441 –1.4380 –2.4591 –2.5604 –1.4142 –1.1090 –3.1041 –0.6415 –1.7598 –1.3571 –0.7634 –0.7324 –1.6569 –2.0970 –2.2575 –2.4419 –1.5072 –0.8513 2logFC

b c d e f g 87y siFoxM1 25 50 4 30 altered genes altered genes **** 4 **** (3309) (5841) ** 1372 1937 3904 40 3 3 ** 20 ** 20 30 15 Overlap 87y vs siFoxM1 GO terms p value 2 2 Cell cycle 1.8E–18 20 Cell cycle process 2.8E–18

Cell cycle phase 1.9E–15 -gal positive cells (%) 10 = 1010 β Mitosis 2.0E–15 1 10 n

1 53BP1+/p21+ cells (%) Nuclear division 2.0E–15 SA-

NEB-anaphase onset (min) 10

Organelle fission 4.2E–15 = 481 M phase of mitotic cell cycle 5.1E–15 n BN cells with mis-segregation (%) = 327 = 224 = 817 = 134 = 188 = 5117 = 3594 Aneusomy index of Chr 7+12+18 (%) M phase 1.8E–14 = 464 n n n n n n n Mitotic cell cycle 7.0E–14 0 0 0 n 0 0 Cell division 1.2E–13 10y 10y + 10y 10y + 10y 10y + 10y 10y + 10y 10y + siFoxM1 siFoxM1 siFoxM1 siFoxM1 siFoxM1

h i Senescence core signature genes Down Up SASP genes

1 –1 1 –1 10y 10y siCtr siCtr –0.5 –0.5 2 2 0 0 1 1 0.5 0.5 10y 10y 2 1 2 1 siFoxM1 siFoxM1 Column Column IL6 AXL IL11 IL1B HGF IL6R Z score ICE1 Z score SMO PLK3 NTF3 KLC1 CCL2 FGF2 FGF7 GLB1 NOL3 MST1 IL1R1 DDA1 GBE1 BDNF UFM1 Gene RAI14 Gene GDNF PCIF1 DGKA MMP1 MMP3 SPIN4 TIMP1 TIMP2 ARID2 MEIS1 TAF13 ICAM1 ICAM3 symbol symbol ZC3H4 P4HA2 CXCL1 CXCL2 CXCL3 CXCL6 KCTD3 C2CD5 PDS5B STAG1 LMNB1 CNTLN SUSD6 VEGFA MMP10 MMP12 CCND1 GSTM4 CHMP5 ZNHIT1 RHNO1 ADPGK IGFBP2 IGFBP4 IGFBP6 PDLIM4 MT-CYB DYNLT3 PLXNA3 SPATA6 POFUT2 ACADVL CDKN1A CDKN2A TRDMT1 CREBBP SLC10A3 SLC16A3 B4GALT7 FAM214B TSPAN13 TMEM87B TNFRSF1B CXCL8 (IL8) TNFRSF11B TNFRSF10C TNFRSF10D 0.3988 0.8716 0.5601 2.3710 0.7014 0.3950 0.4564 1.4476 0.4913 0.3300 1.3513 0.7076 0.9101 0.7975 0.1641 1.1454 0.5961 1.7577 0.3401 0.1210 0.1690 0.3386 0.1722 0.2344 0.6246 0.4351 0.1638 0.6559 2logFC –0.1931 –0.5151 –0.3307 –0.6556 –0.3552 –0.7202 –0.1550 –0.9394 –1.4133 –1.8776 –0.2342 –0.3848 –0.6394 –0.5246 –0.3385 –0.2257 –0.2119 1.6589 2.3713 2.4995 1.3184 2.4843 1.3046 0.6553 1.9565 0.4926 1.2229 0.5372 2.2144 0.7734 0.6308 2.0106 0.6582 0.6974 2.9755 0.7613 1.1932 2.0288 1.8938 3.4351 2.0967 2.2943 2.0232 0.7671 0.7894 1.5024 1.2223 1.9641 2.2582 0.4209 2logFC –0.8118 –1.3087 –0.8571 –2.7033 –0.5451 Fig. 5 FoxM1 repression dictates cellular phenotypes associated with aging. a Heatmap of genes within the “mitotis” GO term differentially expressed between control and FoxM1 siRNA-depleted 10-year-old fibroblasts (2logFC cutoff value < −0.5 and > 0.5, p-value < 0.05, FDR < 5%, Supplementary Data 8). b Venn diagram illustrating the overlap between genes altered in 87 y and FoxM1 siRNA-depleted fibroblasts and the top ten altered GO terms (Supplementary Data 9). c Mitotic duration (NEB-anaphase onset) of control and FoxM1 siRNA-depleted fibroblasts. d Aneusomy index in interphase FISH. e Chromosome mis-segregation rate in CytoD-FISH. f, g Percentage of cells staining positive for the senescence markers β-galactosidase (f) and 53BP1/ p21 (g). h Heatmap of SASP and senescence (CDKN1A, CDKN2A, GLB1, LMNB1) genes differentially expressed in HDF 10 y and 10 y siFoxM1 (Supplementary Data 10)36, 37. i Heatmap of senescence core signature genes differentially expressed in HDF 10 y and 10 y siFoxM1 (Supplementary Data 11); 2logFCs in red indicate genes behaving differently from expected37. In all heatmaps: p-value < 0.05; genes represented in columns and technical replicates represented in rows; Z-score column color intensities representing higher (red) to lower (blue) expression. Values are mean ± SD of three independent experiments. Sample size (n) is indicated in each graph. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 by two-tailed Mann–Whitney (c) and χ2 (d–g) statistical tests modifications, H3K9me3 and H4K20me352, and lamin B1 selective clearance of senescent cells can greatly postpone levels53) were additionally found altered in elderly cells with aging31,55. Our results bring insight into how senescent cells arise segregation defects (presence of micronucleus) vs. elderly cells and provide a molecular basis to delay senescence and thus, a without segregation defects (Supplementary Fig. 10). Altogether, potential strategy against aging and age-associated diseases. our data support a model in which proliferating naturally aged Previous studies have suggested G2 and 4N G1 (mitosis skip) cells with SA gene expression signature (early senescence) lose as the phase at which senescent cells exit the cell cycle56,57. mitotic fidelity, and generate aneuploid progeny that significantly However, these studies made use of the acute senescence stimuli, accounts for the accumulation of full senescent phenotypes gamma irradiation, and oncogenic Ras overexpression, respec- (permanent cell cycle arrest) (Fig. 8). Reinstating FoxM1 tran- tively. In contrast to acute senescence, chronic senescence results scriptional activity in elderly cells ameliorates cell autonomous from long-term, gradual macromolecular damage caused by and non-autonomous feedback effects between mitotic fidelity stresses during lifespan (e.g., loss of proteostasis, DNA damage, and senescence, suggesting that this mechanism evolved as a epigenetic changes). We demonstrate that in a natural aging positive feedback loop between cellular aging and aneuploidy. cellular model, consisting of dermal fibroblasts retrieved from elderly donors and cultured under limited passage number to prevent replicative in vitro aging, senescent cells are often aneu- Discussion ploid as the result of defective chromosome segregation. None- Aging is the largest risk factor for most diseases54. In recent years, theless, as shown for oncogene-induced senescence and seminal studies have shown that the accumulation of senescent replicative senescence57,58, one round of cell division is likely cells in tissues over time shortens healthy lifespan and that required for a transition from early to fully senescent state.

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 9 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6

Consistent with this idea of senescence phenotype evolution, our supporting that micronuclei generated during defective data disclosed the interesting finding that increased pro- mitoses are a key source of immunostimulatory cytosolic DNA inflammatory response is a characteristic of aged cells that are that triggers a cGAS-STING-mediated pro-inflammatory still proliferating, and that chromosome mis-segregation events in response59–61. Whether the evolution of SASP during natural these cells are sufficient to trigger transition into permanent cell aging is dependent of cytosolic DNA signaling is an interesting cycle arrest (full senescence). This is in line with recent findings question to address in the future.

a NEB ANA 87y empty vector

0:00 6:00 12:00 18:00 24:00 30:00 34:30 39:00 51:00 87y + FoxM1 dNdK

0:00 4:30 9:00 13:30 18:00 25:30 27:00 31:30 42:00

b Significantly different among ‘mitosis’ genes

1 –1

–0.5 HDF 87y 2 empty vector 0 1 0.5

2 1 HDF 87y

FoxM1 dNdK Column CIT PBK

OIP5 Z score PLK1 FZR1 TPX2 SKA2 SKA3 SKA1 NUF2 NEK2 NEK6 BUB1 BUB3 EML4 CDK1 CDK2 TUBB NDE1 ANLN KIF22 KIF23 KIF15 KIF11 MAP9 BOD1 CCNF SMC2 SMC4 SGO1 WEE1 ASPM BORA KIF2C Gene BIRC5 ESPL1 SPC24 CEP55 PTTG1 NDC80 KNTC1 CDC20 CKAP5 BUB1B symbol HAUS8 CD2AP UBE2C SPAG5 KIF20B CCNB2 CENPF CDCA2 CDCA3 CCNA2 CCNB1 NEDD9 CDCA5 CDCA8 CENPE CENPV AURKA AURKB NCAPH CCNG1 CCNG2 NCAPG INCENP ZC3HC1 MAD2L1 MAD2L2 ERCC6L CDC25B FAM83D DLGAP5 LRRCC1 CDC25C NUSAP1 NCAPD2 NCAPG2 0.777 0.647 0.816 0.725 0.9462 0.7418 1.0734 0.6732 1.1182 0.7737 0.9529 0.5896 0.5531 0.7415 0.9437 0.7461 0.9185 0.8107 0.9517 0.7266 0.7007 0.9190 1.0623 0.5613 0.7061 1.0897 0.7253 0.8857 0.6635 0.7368 0.9029 0.9362 0.6480 0.6944 0.5084 0.9879 0.8639 1.1294 0.7284 1.1199 0.8161 0.5763 0.7259 0.6812 0.8564 0.6067 1.0297 0.9171 0.7326 0.5806 0.7994 0.6365 0.8511 1.2200 0.9212 0.5028 0.7499 0.8288 0.7399 0.7628 0.7130 0.9416 0.6011 0.7782 0.5507 0.5671 0.5197 0.5933 0.7853 0.8417 0.7686 0.5364 0.8837 0.6406 0.5384 2logFC –0.7217 –0.6902 –0.5327 –0.9404

c defg 25 h20 Mitosis genes 40 **** 4 4 * *** siFoxM1 FoxM1 dNdK 20 (143) ** (79) 30 3 3 15 26 15 54 **** 3 20 2 2 10 50 10 -gal positive cells (%) n= 931 β 10 1 n= 5081 1 5 13 5 53BP1+/p21+ cells (%)

8 SA- NEB-anaphase onset (min) = 625 = 679 = 1213 = 967 = 148 = 252 = 457 HDF 87y = 6178 BN cells with mis-segregation (%) n n n n n n n n (71) 0 Aneusomy index of Chr 7+12+18 (%) 0 0 0 0

84/87y 84/87y 84/87y 84/87y 84/87y 84/87y + 84/87y + 84/87y + 84/87y + 84/87y +

FoxM1dNdK FoxM1dNdK FoxM1dNdK FoxM1dNdK FoxM1dNdK

i j Senescence core signature genes Down Up SASP genes

1 1 1 1

vector 0.5 2 vectorr 2 0.5 87y empty 0 87y empty 0 1 –0.5 1 –0.5 –1 dNdK 2 2 –1 dNdK 87y FoxM1 Column 87y FoxM1 Column

MIF Z score AXL Z score IL11 PGF IL6R ICE1 NFIA SMO PLK3 CCL2 FGF2 FGF7 PLAU NOL3 MST1 IL1R1 IL6ST GBE1 BDNF BMP6 GDNF DGKA MMP1 MMP3 KITLG SCOC TIMP1 Gene Gene TAF13 MEIS1 ICAM3 ZC3H4 P4HA2 symbol symbol CXCL1 CXCL3 CXCL6 KCTD3 PDS5B STAG1 LMNB1 PLAUR CNTLN SUSD6 MMP10 CCND1 TOLLIP RHNO1 ZNHIT1 CHMP5 ADPGK IGFBP2 IGFBP6 IGFBP7 PDLIM4 ZBTB7A MT-CYB DYNLT3 PLXNA3 SPATA6 USP6NL POFUT2 ACADVL CDKN1A CDKN2A CREBBP TSPAN13 FAM214B TNFRSF1B ARHGAP35 CXCL8 (IL8) TNFRSF11B TNFRSF10C TNFRSF10D 0.6449 2.3114 1.7644 1.6053 0.1495 0.6926 1.8202 0.5913 3.8620 1.0044 1.4084 1.4512 0.5369 4.4747 0.2528 0.2386 3.5368 0.5146 0.8079 0.5938 0.5399 1.0469 0.5689 1.2773 7.3223 2.1435 0.7217 1.4861 1.7680 0.4315 0.7855 1.3518 1.1610 0.2117 0.5218 0.2838 0.1200 0.1984 0.2690 0.8164 0.1365 0.7392 2.4960 0.4885 0.1290 0.4597 0.2248 0.2949 0.2743 0.4000 0.1234 0.2568 0.4676 1.0819 0.3352 0.1946 1.2835 0.8673 0.9412 0.5318 0.6361 0.5182 0.4314 0.1458 0.2651 0.4888 0.1963 2.2360 0.3251 0.3995 1.6372 1.3793 2logFC 2logFC – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –

10 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

There is still little to no direct evidence demonstrating that Possible explanations are the premature killing of mice before aneuploidy per se is a driver or facilitator of aging. In our study they start developing aging phenotypes later in life and the cur- we aimed to understand the exact causal network between age- sory analysis for overt age-related degeneration missing tissue- associated aneuploidy and senescence. Using innovative experi- specific phenotypes14. Alternatively, aneuploidy-associated genes mental layouts, such as aneuploidy measurement in FACS-sorted that are strongly linked with premature aging might require senescent cells with high SA-β-gal activity and long-have induction of mild levels of aneuploidy or counteracting functions demonstrated that aneuploidization in an aging cell context in additional cellular stresses that engage senescence response ultimately triggers permanent cell cycle arrest and full senescence. pathways. This appears to be the case of FoxM1. FoxM1 We showed that the frequency of mitotic abnormalities repression translates into mild aneuploidy levels and may also increases in older cells, resulting in mild aneuploidy levels, and further act by counteracting age-associated cellular damage identified the FoxM1 transcription factor as the molecular caused by genotoxic and oxidative stresses43,65. Interestingly, determinant of this age-associated mitotic decline. FoxM1 increased FoxM1 expression was shown to improve liver- repression is likely mediated by activation of stress pathways, regenerating capacity in older mice42 and lung regeneration fol- presumably triggered by primary causes of cellular damage, such lowing injury66. However, further evidence shows that FoxM1 is as genomic instability or loss of proteostasis. For instance, it has elevated in human cancers, thus questioning its potential for anti- been shown that genotoxic stress can activate the p53-p21- aging therapy. Thus far, FoxM1 has only been shown to be DREAM pathway, which in turn prevents early cell cycle gene tumorigenic if tumor suppressor genes are lost or oncogenic expression required for FoxM1 transcriptional activity39,62. mutations (such as K-RAsG12D) are present67,68. As we found Although transcriptional deregulation during aging has been that brief reactivation of FoxM1 activity back to the levels of widely reported in asynchronous cell populations63,64, in this young cells in elderly cells rescues the observed aging phenotypes, study we have used synchronized mitotic populations and found we propose that a cyclic FoxM1 induction scheme, starting in that many cell cycle genes were dysregulated in old cells as adulthood, could work safely in vivo. FoxM1 induction acts compared with young cells. Intriguingly, old mitotic cells have not only through modulation of mitotic fidelity and senescence intrinsic low levels of mitotic transcripts. Although this supports pro-inflammatory phenotype, but also by improving the pro- the observed mitotic abnormalities and increased chromosome liferative capacity of fitter (undamaged) cells in the elderly cell mis-segregation rate (e.g., low levels of major regulators of the population that dilute, rather than totally clearing, the full-blown error-correction machinery for chromosome attachments), it is senescent cells, thereby coping with the detrimental but also still surprising how elderly mitotic cells can cope with such beneficial (wound healing, tumor suppression) effects of senes- reduced levels of transcripts, e.g., CCNB1. One possibility might cence. Thus, our findings disclose a molecular mechanism with be the balanced/stoichiometric repression of most mitotic genes. potential clinical benefit to healthy lifespan extension and HGPS Furthermore, parallel mechanisms might buffer aging-mediated treatment. repression of mitotic transcripts. For example, even though we found SAC genes to be downregulated in elderly cells, SAC functionality was similar in young and old cells, suggesting that Methods concurrent downregulation of genes contributing to proteasome Cell culture. A total of 11 human fibroblast cultures, established from skin samples of Caucasian males with ages ranging from neonatal to octogenarian (two biolo- activity (e.g., Cdc20 and APC/C subunits) might buffer SAC gene gical samples per age), were acquired from cell biobanks as summarized (Sup- repression. plementary Table 1). Several time points over the human lifespan were included to We demonstrated that re-establishment of FoxM1 expression reinforce the validity of any correlation found. All donors were reported as in elderly and HGPS fibroblasts can rescue mitotic decline and “healthy”, except the 8-year-old donor diagnosed with the Hutchison–Gilford progeria. HDFs were seeded at 1 × 104 cells per cm2 of growth area in minimal delay senescence. Fibroblasts are the main constituents of con- essential medium Eagle–Earle (MEM) supplemented with 15% fetal bovine serum nective tissue and are important factors in extracellular matrix (FBS), 2.5 mM L-glutamine, and 1× antibiotic–antimycotic (all from Gibco, production and tissue homeostasis. Therefore, delayed accumu- Thermo Fisher Scientific, CA, USA). Only early passage dividing fibroblasts (up to lation of senescent fibroblasts might counteract a SASP-induced passage 3–5) with cumulative population doubling level PDL < 24 were used in all = − + = inflammatory microenvironment in these tissues and help to experiments. PDL 3.32 (log UCY log l) X, where UCY the cell yield at that point, l = the cell number used to begin that subculture, and X = the doubling level protect stem cell and parenchymal cell functions. Re-expression of the cells used to initiate the subculture. PD = T*[ln2/ln(Xe/Xi)], where T = time of FoxM1 could thus protect against aging of adult stem cell and interval (hours) between two consecutive cell passages, Xe = number of cells col- post-mitotic tissues. Indeed, increased expression of one FoxM1 lected at culture passaging, and Xi = number of cells seeded to initiate subculture. fi ’ fi ’ transcriptional target, BubR139, was previously shown to prevent Murine adult broblasts (MAFs) were cultured in Dulbecco s modi ed Eagle s 13 medium (DMEM) supplemented with nutrient mixture F12, 10% FBS, L-glutamine, aneuploidization and delay aging . However, other aneuploidy and antibiotic–antimycotic (all from Gibco). All cells were grown at 37 °C and fi mouse models have not been reported to exhibit premature aging. humidi ed atmosphere with 5% CO2.

Fig. 6 Constitutively active FoxM1 ameliorates mitotic fitness and aging markers in elderly cells. a Movie frames of elderly dividing cells expressing H2B–GFP/α-Tubulin–mCherry (upper panel) and H2B–GFP/α-Tubulin–mCherry + FoxM1-dNdK (lower panel) (Supplementary Movies 5, 6). Time, min:s. Scale bar, 5 µm. b Heatmap of genes within the “mitosis” GO term differentially expressed in mitotic elderly cells transduced with lentiviral empty vector or vector expressing FoxM1-dNdK (2logFC cutoff value < −0.5 and > 0.5, p-value < 0.05, FDR < 5%, Supplementary Data 13). c Venn diagram illustrating the overlap between mitosis genes altered in 87 y, 10 y FoxM1 siRNA-depleted, and 87 y FoxM1-dNdK-expressing fibroblasts (Supplementary Data 14). d Mitotic duration (NEB to anaphase onset) in elderly fibroblasts infected with control and FoxM1-dNdK lentiviruses. e Aneusomy index in interphase FISH. f Chromosome mis-segregation rate in CytoD-FISH. g, h Percentage of cells staining positive for the senescence markers β-galactosidase g and 53BPl/p2l h. i Heatmap of SASP and senescence (CDKN1A, CDKN2A, LMNB1) genes differentially expressed in HDF 87 y and 87 y FoxM1-dNdK (Supplementary Data 15); 2logFCs in red indicate genes behaving differently from expected36, 37. j Heatmap of senescence core signature genes’ expression in 87 y and 87 y FoxM1-dNdK (Supplementary Data 16); 2logFCs in red indicate genes behaving differently from expected37. In all heatmaps, p-value < 0.05; genes represented in columns and technical replicates represented in rows; Z-score column color intensities representing higher (red) to lower (blue) expression. Values are mean ± SD of three independent experiments. Sample size (n) is indicated in each graph. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 by two-tailed Mann–Whitney (d) and χ2 (e–h) statistical tests

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 11 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6

Isolation of mouse ﬁbroblasts. Sv/129 mice were housed and handled accord- Drug treatments. Fibroblasts were incubated for 24 h in medium containing 2 µg/ ingly to European Union and MAFs were collected from ears of n > 3 sv/129 ml cytochalasin D (C8273, Sigma-Aldrich, MO, USA) to block cytokinesis. To females of the same litter at their age of 8 weeks, 6 months, 1 year, 1.5 years, and 2 inhibit the SAC, cells were treated with 5 µM Mps1 inhibitor (AZ3146, TOCRIS, years. Ears were washed with phosphate-buffered saline (PBS), cut into small USA). To induce chronic activation of the SAC, cells were treated with 100 nM pieces, and incubated with 1 mg/ml collagenase D and 1 mg/ml collagenase/dispase Taxol (Sigma-Aldrich, MO, USA) and 5 µM and STLC (2799-07-7, Tocris). For (both from Roche Applied Science, Germany) in DMEM:F12 without FBS, for 45 proteasome activity enhancement, 10 µM of Usp14 inhibitor were used (I-300, min at 37 °C and 5% CO2. Cells were then grown on a six-well dish containing BostonBiochem, Cambridge, MA). To inhibit kinesin-5, STLC (Tocris) was used at DMEM:F12, supplemented with 10% FBS and antibiotic–antimycotic. 5 µM during 16 h, to enrich the MI for mitotic cell shake-off.

a bcd 250 K N/N 250 K 84/87y 250 K N/N 250 K 84/87y siFoxM1 dNdK 200 K 200 K 200 K 200 K

150 K 150 K 150 K 150 K SSC-A SSC-A SSC-A SSC-A 100 K 100 K 100 K 100 K

50 K 50 K 50 K SA--gal: 50 K SA--gal: SA--gal: 3.71% SA- -gal: 9.83% 22% 18.1% 0 0 0 0 100 101 102 103 104 105 100 101 102 103 104 105 100 101 102 103 104 105 100 101 102 103 104 105 APC-A APC-A APC-A APC-A ef 12 * 100 ** N/N *** N/N siFoxm1 10 ns 84/87y *** 80 84/87y dNdK 8 *** 60 * 6 ** 40

Events (%) 4 Aneuploidy (%)

20 = 981 2 = 1026 n n

= 170 = 1296 = 400 = 923 = 413 = 1460 n n n n n n

0 0 101 102 103 104 105 ø β-gal+ ø β-gal+ ø β-gal+ ø β-gal+ DDAOG fluorescence intensity N/N 84/87y N/N 84/87y siFoxM1 FoxM1 dNdK

g h HDF 87y H2B-GFP

–00:15 00:00 00:25 00:30 00:55 03:55 Mitotic cell tracking Daughter cells tracking Plate cells Live-cell imaging End imaging -Gal assay segregation β Correct chromosome 53BP1/p21 staining Image acquisition SA- Image acquisition –24 h0 h 24 h 48 h 72 h (daughter cells cycle) 14:55 21:25 21:50 22:05 22:10 22:40

i correct chromosome chromosome segregation mis-segregation –00:10 00:00 00:25 00:30 00:35 01:05 n =39 mitosis n =21 mitosis (78 daughter cells) (42 daughter cells)

Die? Die? 2:00 12:00 24:00 36:00 48:00 62:50 H2B-GFP SA-β-Gal p21 53BP1

100% 100% (daughter cells don’t cycle) NO NO Correct chromosome segregation

71.7±0.4% Cycle? Cycle? YES

28.3±0.4% 100% NO NO

–00:10 00:00 00:10 00:45 01:00 01:35

Senesce? Senesce?

01:40 02:0508:00 24:0034:00 48:00 H2B-GFP SA-β-Gal p21 53BP1

YES NO YES NO (daughter cells don’t cycle) Chromosome mis-segregation β-Gal+ 13.4±0.9% 86.6±0.9% β-Gal+ 46.4±3.6%* 53.6±3.6%

53BP1+ 53BP1+ 24.1±11.6% 75.9±7.1% 85.7±7.1%**** 14.3±7.1% /p21+ /p21+

12 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

Fluorescence in situ hybridization. FISH analysis was used to measure aneusomy Immunostaining. Fibroblasts were grown on sterilized glass coverslips coated with index (Interphase FISH; Figs. 1a, 5d, 6e, 7f and Supplementary Fig. 9e) and 50 µg/ml fibronectin (F1141, Sigma-Aldrich, MO, USA). Cells were fixed in freshly chromosome mis-segregation rate (CytoD FISH; Figs. 1b, 5e, 6f and Supplementary prepared 4% paraformaldehyde in PBS for 20 min. Following fixation, cells were Fig. 9f). “Interphase FISH” measures the prevalence of somatic aneuploidy by the rinsed in PBS and permeabilized in PBS + 0.3% Triton-X100 for 7 min. Cells were ratio of aneusomic cells for chromosomes 7, 12, and 18 to the total cell count for a next blocked in 10% FBS in PBS-T (PBS + 0.05% Tween-20) for 1 h and then sample ( > 2500 nuclei) (aneusomy index). “CytoD FISH” measures the rate of incubated overnight at 4 °C with primary antibodies diluted in PBS-T + 5% FBS as chromosome mis-segregation (number of events in which two sister chromatids follows: rabbit anti-53BP1 (4937, Cell Signaling Technology, MA, USA), 1:100; co-segregate to the same daughter cell) by combining a cytokinesis-block assay mouse anti-p21 (SC-6246, Santa Cruz Biotechnology, CA, USA), 1:1000; rabbit (cytochalasin D 24 h treatment) with FISH staining. “CytoD FISH” measures the anti-FoxM1 (13147, ProteinTech Group, Inc., IL, USA), 1:1500; mouse anti-Cdc20 percentage of BN telophases exhibiting chromosome 7, 12, and 18 mis-segregation (SC-5296, Santa Cruz Biotechnology), 1:100; mouse anti-Cyclin B (SC-245, Santa over the total BN cell count for a sample ( > 200 BN cells). For both Interphase and Cruz Biotechnology), 1:1000 secondary antibodies AlexaFluor-488 and -568 (Life CytoD FISH, fibroblasts were grown on Superfrost™ Plus microscope slides Technologies, CA, USA) were diluted 1:1500 in PBS-T + 5% FBS. DNA was (Menzel, Thermo Scientific, CA, USA) placed in a quadriperm dish (Sarsted, counterstained with 1 µg/ml DAPI (Sigma-Aldrich, MO, USA). Coverslips were Nümbrecht, Germany). Cells were given a hypotonic shock during 30 min (0.03 M mounted in slides with mounting solution (90% glycerol, 0.5% N-propyl-gallate, sodium citrate, Sigma-Aldrich, MO, USA), followed by fixation in ice-cold Carnoy 20 nM Tris, pH 8). fixative added drop-wise and incubated for 5 min. This step was repeated two more times. FISH was performed with the Vysis centromeric probes CEP7 Spectrum Telomere PNA FISH. Fibroblasts were incubated in 0.05 µg/ml colcemid Aqua, CEP12 Spectrum Green, and CEP18 Spectrum Orange (Abbott Laboratories, (15212012, Gibco, Thermo Fisher Scientific) for 4 h, to induce metaphase arrest. Chicago, IL, USA) according to manufacturer’s instructions. Slides were mounted Following trypsinization, fibroblasts were incubated in 0.03 M sodium citrate for with mounting medium containing DAPI (Vectashield, Vector Laboratories, CA, 30 min at 37 °C. Cells were then fixed in freshly made Carnoy fixative solution and USA) and scored blindly. stored at 4 °C. Metaphase spreads were fixed with 4% formaldehyde in PBS for 2 min, followed by pepsin digestion (1 mg/ml) for 10 min at 37 °C. After a dehy- dration step with ethanol, dried slides were hybridized with Telomere PNA probe Apoptosis assay. Programmed cell death (apoptosis) was evaluated by flow (Applied Biosystems, CA, USA) (0.5 µg/ml) in 10 mM Tris pH 7.5, 70% for- cytometry using fluorescein isothiocyanate (FITC)-conjugated Annexin V/Apop- mamide, 0.25% blocking reagent (Roche, Germany), 2 mM MgCl , 700 µM citric fl 2 tosis detection kit (BioLegend, Inc. San Diego, CA). Brie y, cells were washed twice acid, 7 mM Na2HPO4, for 3 min in a hot plate at 80 °C and then for 2 h at 37 °C in in cold cell staining buffer and resuspended in 100 µL of Annexin V-binding buffer. humidified chamber. Slides were washed in 70% formamide, 10 mM Tris, 0.1% Subsequently, 5 µL of FITC-Annexin V were added to cell suspension. Cells were bovine serum albumin twice for 15 min, then washed three times in Tris-buffered incubated for 15 min in the dark, washed with Annexin V-binding buffer, and saline (TBS) for 5 min, and finally mounted with mounting media containing analyzed immediately by flow cytometry. DAPI (Vectashield, Vector Laboratories).

Phase-contrast live-cell imaging. Fibroblasts were grown in glass-bottom 35 mm β fi SA- -gal assay.In xed-cell analysis, cells were incubated for 90 min in medium µ-dishes (Ibidi GmbH, Germany), coated with 50 µg/ml fibronectin (F1141, Sigma- fi with 100 nM Ba lomycin A1 (B1793, Sigma-Aldrich, MO, USA) to induce lyso- Aldrich, MO, USA). Images were acquired on a Zeiss Axiovert 200 M inverted μ β fl somal alkalinization. Fluorogenic substrate (33 M) for -galactosidase, uorescein microscope (Carl Zeiss, Oberkochen, Germany) equipped with a CoolSnap camera β di- -D-galactopyranoside (F2756, Sigma-Aldrich, MO, USA) were then added to (Photometrics, Tucson, USA), XY motorized stage and NanoPiezo Z stage, under fi the medium, and incubation carried out for 90 min. Cells were xed in 4% par- controlled temperature, atmosphere, and humidity. Neighbor fields (20–25) were aformaldehyde for 15 min, rinsed with PBS, and permeabilized with 0.1% Triton- imaged every 2.5 min for 2–3 days, using a ×20/0.3 numerical aperture (NA) A- X100 in PBS for 15 min. Finally, cells were counterstained with 1 µg/ml DAPI Plan objective. Stitching of neighboring fields was done using the plugin “Stitch fi (Sigma-Aldrich, MO, USA). For FACS, cells were incubated in Ba lomycin A1 as Grid” (Stephan Preibisch) from ImageJ/Fiji software. described above and then exposed to 10 μMoffluorogenic substrate for β-galactosidase, DDAOG (9H-(1,3-dichloro-9,9-dimethylacridin-2-one-7-yl) β-D-Galac- topyranoside), for 90 min (Setareh Biotech LLC, USA). Live-cell and fixed-cell correlative microscopy. Eighty-seven-year-old fibroblasts expressing H2B–GFP were grown in µ-Slide 2 Well ibiTreat (Ibidi GmbH) and analyzed accordingly to the experimental layout shown in Fig. 7i. Images were acquired on a Leica DMI6000b inverted microscope (Leica Microsystems, Ger- Fluorescence-activated cell sorting. FACS sorting was used to isolate sub- many), equipped with an ORCA-Flash4.0 camera (Hamamatsu, Japan), using the populations of senescent (SA-β-gal positive) live fibroblasts. FACS sorting was laser line 488 nm for the excitation of green fluorescent protein (GFP), and under performed in FACSAria™ I Cell Sorter (BD Biosciences, CA, USA), using the laser controlled temperature, atmosphere and humidity. Neighbor fields (60–70) were line of 633 nm. All cells within a single experiment were detected using the same imaged every 5 min for 3–4 days, using a ×20 LD/0.4 NA objective (Leica voltage settings and sorted using an 85 μm nozzle. Cells were initially gated by Microsystems). Following the long-term live-cell imaging, cells were processed for forward scatter area (FSC-A) vs. side scatter area, which excludes dead cells and SA-β-gal assay and 53BP1/p21 double immunostaining as described elsewhere in subcellular debris, with subsequent exclusion of cell doublets and clumps through this section, and the same neighbor fields acquired using a ×40 LD/0.6 NA FSC-A vs. FSC-width plot. The signal was detected using the APC-A channel. The objective. LAS X software (Leica Microsystems) was used for image acquisition and relative β-galactosidase activity was inferred from the median fluorescence intensity analysis. of the population. The sorting gates were designed accordingly to the respective auto-fluorescent control. Cells were sorted directly into MEM with 15% FBS and seeded in Superfrost™ Plus microscope slides for subsequent FISH analysis. Ana- Spinning-disk confocal microscopy. Four-dimensional data sets were collected lysis of FACS data was done using FlowJo v10 software (TreeStar, Inc., Ashland, with Andor Revolution XD spinning-disk confocal system (Andor Technology, OR). Belfast, UK), equipped with an electron-multiplying charge-coupled device

Fig. 7 FoxM1 governs aneuploidization-driven cellular senescence in elderly cells. a–d FACS sorting of senescent cells from neonatal a, elderly b, FoxM1 siRNA-depleted neonatal c, and 84 y/87 y with FoxM1-dNdK d cell populations with high β-galactosidase activity. The gates were defined accordingly to the respective auto-fluorescent control. e Relative intensity levels of the fluorogenic substrate DDAOG in the sorted cell populations. f Aneuploidy index in FACS-sorted β-gal-positive fibroblast subpopulations (β-gal +) vs. unsorted populations (∅) as determined by FISH analysis for three chromosome pairs. g Experimental layout of live-cell/fixed-cell correlative microscopy analysis shown in h, i. Mitotic elderly fibroblasts expressing H2B–GFP and respective daughter cells were imaged for 72 h. SA-β-Gal assay and immunostaining for 53BP1/p21 were performed at the end of imaging. h Movie frames of representative phenotypes observed for elderly cells expressing H2B–GFP. Top panel, correct chromosome segregation, with cycling daughter cells (Supplementary Movie 9). Middle panel, correct chromosome segregation with non-cycling daughter cells staining negative for SA-β-Gal and 53BP1/p21 (Supplementary Movie 10). Bottom panel, chromosome mis-segregation leading to micronuclei formation (arrowheads), with non-cycling daughter cells staining positive for senescence markers (SA-β-Gal and 53BP1/p21) (Supplementary Movie 11). Dashed line indicates the tracked daughter cell. Time, hour: minute. Scale bar, 30 µm (movie frames) and 15 µm (immunostaining). i Single-cell analysis of daughter cell fate (cell death, cell cycle arrest, and cell senescence) from mitoses with apparent correct chromosome segregation or with mis-segregation (leading to micronuclei formation). Non-cycling daughter cells were stained for senescence markers (β-gal and 53BP1/p21). Values are mean ± SD of two independent experiments. Sample size (n)is indicated for f and i. NS, p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 by two-tailed χ2 statistical tests

NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications 13 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6

Young fibroblasts

Natural aging

Old mitotic cell Aneuploid daughter cells Old fibroblasts

Aging Aneuploidy Aging 1. Early senescence 2. Loss of mitotic fidelity 3. Full senescence

Genetic damage Chromosome mis-segregation Aneuploidy FoxM1 mitotic senescence gene signature Genetic damage Proliferation rate Foxm1 Senescence markers Proliferation rate feedback loop feedback

Aging-aneuploidy SASP SASP Aneuploidy

Short-term induction of foxM1

Rejuvenated old fibroblasts

FoxM1 Mitotic fidelity Aneuploidy Senescence SASP

FoxM1 p21 signalling DNA damage SA-β−gal activity SASP

Fig. 8 Positive feedback loop between aging and aneuploidy. Model summarizing the molecular basis of age-associated mitotic decline and accumulation of senescent cells induced by aneuploidy. FoxM1 repression in aged dividing cells with senescence gene signature (1. early senescence) leads to general dysfunction of the mitotic machinery and increased chromosome mis-segregation rate (2. loss of mitotic fidelity). The aneuploid progeny stops proliferating exhibiting aggravated senescence phenotypes (3. full senescence) with pro-inflammatory impact in neighboring pre-senescent cells. FoxM1 induction in old cells improves mitotic fitness and delays the accumulation of senescent cells iXonEM Camera and a Yokogawa CSU 22 unit based on an Olympus IX81 equipped with a Photometrics CoolSNAP K4 camera and using a Nikon ×20/0.45 inverted microscope (Olympus, Southend-on-Sea, UK). Two laser lines at 488 and NA Plan Fluor objective. User-defined fluorescence intensity thresholds were set 561 nm were used for the excitation of GFP and mCherry and the system was and used consistently for samples within each experiment. driven by Andor IQ software. Z-stacks (0.8–1.0 μm) covering the entire volume of the mitotic cells were collected every 1.5 min with a PlanApo ×60/1.4 NA objective. All images represent maximum-intensity projections of all z-planes. ImageJ/Fiji Image analysis. Live-cell phenotypes (mitotic duration, spindle positioning, and fi software was used to edit the movies. cytokinesis failure) and xed-cell experiments (FISH, SA biomarkers, and micronuclei) were blindly quantified using ImageJ/Fiji software.

Fluorescence microscopy. Analysis of the SA-β-gal fluorescence assay was carried out on a Zeiss AxioImager Z1 (Carl Zeiss) equipped with an Axiocam MR and Western blotting. Mitotic cell populations were collected by shaking-off cell fl using an EC-Plan-Neofluor ×40/1.3 NA objective. Cells displaying > 5 fluorescent culture asks enriched for MI by a 16 h treatment with STLC. MI > 95% was granules were considered positive for SA-β-gal activity. Image acquisition of determined by visual scoring of cells with condensed chromosomes after Carnoy fi FoxM1, Cyclin B, and Cdc20 immunostaining was performed on a Zeiss AxioI- xation, followed by with 1 µg/ml DAPI in PBS. Lysis buffer (150 nM NaCl, 10 nM mager using a Plan-Apochromat ×63/1.4 NA objective. Prometaphase cells were Tris-HCl pH 7.4, 1 nM EDTA, 1 nM EGTA, 0.5% IGEPAL) with protease inhi- fi acquired with 0.24 μM Z-stacks. Image acquisition of H4K20me3, H3K9me3, and bitors was added to mitotic cell pellets, and lysates quanti ed for protein content by ™ Lamin B1 immunostaining was performed on Leica 6000B using a ×40 LD/0.6 NA the Lowry Method (DC Protein Assay, Bio-Rad, CA, USA). Twenty micrograms objective. LAS X software (Leica Microsystems) was used for image acquisition and of total extract were then loaded in SDS-polyacrylamide gel electrophoresis gels cells were acquired with 0.44 μM Z-stacks. User-defined fluorescence intensity and transferred onto nitrocellulose membranes for western blot analysis. Mem- thresholds were set and used consistently for samples within each experiment. branes were blocked during 1 h with TBS containing 5% low-fat milk. Primary AutoQuant X2 (Media Cybernetics, Rockville, USA) was used for image antibodies were diluted in TBS containing 2% low-fat milk as follows: rabbit anti- deconvolution. FoxM1 (13147, ProteinTech Group, Inc.), 1:1000; mouse anti-Cyclin B (SC-245, Santa Cruz Biotechnology), 1:1000, mouse anti-Ndc80 (clone 9G3, Abcam, Cam- bridge, UK), 1:1750; mouse anti-Plk1 (SC-17783, Santa Cruz Biotechnology), 1:100; Automated microscopy. Image fields of 53BP1/p21 double immunostaining and mouse anti α-tubulin (T5168, Sigma-Aldrich, CA, USA), 1:50,000; and mouse anti- FISH staining were acquired on IN Cell Analyzer 2000 (GE Healthcare, UK), GAPDH (60004, ProteinTech Group, Inc.), 1:30,000. Goat anti-rabbit (SC-2004,

14 NATURE COMMUNICATIONS | (2018) 9:2834 | DOI: 10.1038/s41467-018-05258-6 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05258-6 ARTICLE

Santa Cruz Biotechnology) and goat anti-mouse (SC-2005, Santa Cruz Bio- or > 0.5, and FDR < 0.05. For generation of RNA-seq heatmaps, transcript counts technology) horseradish peroxidase-conjugated secondary antibodies were diluted were normalized to the sample library size. These values were subsequently scaled at 1:3000 in TBS containing 2% low-fat milk. Signal was detected using Clarity by gene using normalized scores or z-scores (i.e. a value of 0 corresponds to the Western ECL Substrate reagent (Bio-Rad Laboratories, CA, USA) according to mean gene expression of that gene across all libraries, and ± 1, ± 2, etc. represent 1, manufacturer’s instructions. A GS-800 calibrated densitometer with Quantity One 2, etc. SDs from the gene mean). Hierarchical clustering was performed using the R 1-D Analysis Software 4.6 (Bio-Rad Laboratories) was used for quantitative analysis library heatmap.2. RNA-seq data represent two independent experimental repli- of protein levels. Uncropped scans of all blots in the main manuscript and sup- cates of each biological sample. GO term enrichment analysis of differentially plementary figures are provided in Supplementary Fig. 11. expressed genes was performed using Database for Annotation, Visualization and Integrated Discovery Functional Annotation Tool v6.770 (www.david-d.ncifcrf. gov). To calculate the significance of gene set enrichment, empirical p-values were Lentiviral plasmids. H2B–GFP69 was amplified as a BglII–H2B–GFP–T2A- generated using DAVID tool. BamHI–NotI fragment. This PCR fragment was digested with BglII + NotI and ligated into pRetrox-Tight-Puro (Clontech, CA, USA) digested with BamHI + NotI, thus destroying the 5′ BamHI/BglII site, while reintroducing a BamHI site 3′ Statistical analysis. Sample sizes and statistical tests for each experiment are of H2B–GFP–T2A. In parallel, α-Tubulin69 was amplified as a BglII–α- indicated in the fugure legends. p-values were obtained using GraphPad Prism Tubulin–BamHI–NotI fragment and ligated into pRetrox-Tight-Puro digested with version 6 (GraphPad, San Diego, CA, USA). Data were tested for parametric vs. BamHI + NotI, again destroying the 5′ BamHI/BglII site, while reintroducing a non-parametric distribution using D’Agostino–Pearson omnibus normality test. BamHI site 3′ of α-Tubulin. mCherry was amplified from pExchange-1-Cherry Spearman’s rank correlation, Mann–Whitney, two-tailed χ2, or one-way analysis of (Agilent Technologies, CA, USA) as a BglII–mCherry–NotI fragment and was variance for multiple comparisons tests were then applied accordingly. NS, p > 0.05, ligated into pRetrox–α-Tubulin digested with BamHI–NotI, yielding pRetrox–α- *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001. Values are shown as mean ± Tubulin–mCherry. Finally, α-Tubulin–mCherry was PCR-amplified as a BglII–α- SD or mean ± SEM. Tubulin–mCherry–NotI fragment and ligated into pRetrox–H2B–GFP–T2A digested with BamHI + NotI, yielding pRetrox–H2B–GFP–T2A–α- – – – – – –α Data availability. Raw unaligned sequencing reads (fastq-format) that support Tubulin mCherry. To obtain pLVX Tight-Puro H2B GFP T2A - the findings of this study have been deposited in the ENA and are available tubulin–mCherry, a BglII–H2B–GFP–T2A–α-Tubulin–mCherry–NotI fragment fi – – – –α – under the accession number PRJEB27047. The authors declare that data sup- was ampli ed from pRetroX H2B T2A GFP -Tubulin mCherry and ligated porting the findings of this study are available in the main manuscript and into pLVX–Tight-Puro (Clontech) digested with BamHI + NotI. To generate – – – – – supplemental information, or otherwise available from the corresponding author pLVX Tight-Puro FoxM1-dNdK, a BglII FOXM1 dNdK NotI fragment was upon request. amplified from pcDNA3–Flag-ΔN-ΔKEN–FoxM145 and ligated into pLVX–Tight- Puro digested with BamHI + NotI. Primers used are described in Supplementary Table 4. Received: 8 September 2017 Accepted: 22 June 2018

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Activation of FoxM1 during G2 requires cyclin A/Cdk- TUGAL 2020 through FEDER and by FCT; Foundation Pediatric Oncology Groningen dependent relief of autorepression by the FoxM1 N-terminal domain. Mol. grant and Dutch Cancer Society grant 2012-RUG-5549 to F.F. Cell. Biol. 28, 3076–3087 (2008). 46. Laoukili, J., Alvarez-Fernandez, M., Stahl, M. & Medema, R. H. FoxM1 is degraded at mitotic exit in a Cdh1-dependent manner. Cell Cycle 7, 2720–2726 (2008). Author contributions 47. Andriani, G. A. et al. Whole chromosome instability induces senescence and J.C.M. initiated the project. J.C.M, S.V., and R.R. designed and performed the experi- promotes SASP. Sci. Rep. 6, 35218 (2016). ments, and analyzed the data. B.B. and P.B. performed RNA-sequencing and bioinfor- 48. Baker, D. J. et al. Early aging-associated phenotypes in Bub3/Rae1 matics analysis. J.M.E. performed telomeric-FISH analysis. M.G.F., R.M., and F.F. haploinsufficient mice. J. Cell Biol. 172, 529–540 (2006). contributed to the study design and edited the manuscript. E.L. conceived the idea,

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supervised the work, and wrote the manuscript. All authors discussed results, prepared Open Access This article is licensed under a Creative Commons ﬁ gures, and edited the manuscript. Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give Additional information appropriate credit to the original author(s) and the source, provide a link to the Creative Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467- Commons license, and indicate if changes were made. The images or other third party ’ 018-05258-6. material in this article are included in the article s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the Competing interests: The authors declare no competing interests. article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from Reprints and permission information is available online at http://npg.nature.com/ the copyright holder. To view a copy of this license, visit http://creativecommons.org/ reprintsandpermissions/ licenses/by/4.0/.

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