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Aging in the Cardiovascular System: Lessons from Hutchinson-Gilford Progeria Syndrome
Publication date Created:
February 10 2018
Publication date (Print):
February 10 2018
Journal:
Annual Review of Physiology
Publisher:
Annual Reviews
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Abstract
Aging, the main risk factor for cardiovascular disease (CVD), is becoming progressively more prevalent in our societies. A better understanding of how aging promotes CVD is therefore urgently needed to develop new strategies to reduce disease burden. Atherosclerosis and heart failure contribute significantly to age-associated CVD-related morbimortality. CVD and aging are both accelerated in patients suffering from Hutchinson-Gilford progeria syndrome (HGPS), a rare genetic disorder caused by the prelamin A mutant progerin. Progerin causes extensive atherosclerosis and cardiac electrophysiological alterations that invariably lead to premature aging and death. This review summarizes the main structural and functional alterations to the cardiovascular system during physiological and premature aging and discusses the mechanisms underlying exaggerated CVD and aging induced by prelamin A and progerin. Because both proteins are expressed in normally aging non-HGPS individuals, and most hallmarks of normal aging occur in progeria, research on HGPS can identify mechanisms underlying physiological aging.
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Most cited references101
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Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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The epidemiology of heart failure: The Framingham Study
Kalon Ho, Joan Pinsky, William B Kannel … (1993)
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Recapitulation of premature aging with iPSCs from Hutchinson-Gilford progeria syndrome
Hui Liu, Basam Barkho, Sergio Ruiz … (2011)
Hutchinson-Gilford progeria syndrome (HGPS) is a rare and fatal human premature aging disease1–5, characterized by premature arteriosclerosis and degeneration of vascular smooth muscle cells (SMCs)6–8. HGPS is caused by a single-point mutation in the LMNA gene, resulting in the generation of progerin, a truncated splicing mutant of lamin A. Accumulation of progerin leads to various aging-associated nuclear defects including disorganization of nuclear lamina and loss of heterochromatin9–12. Here, we report the generation of induced pluripotent stem cells (iPSCs) from fibroblasts obtained from patients with HGPS. HGPS-iPSCs show absence of progerin, and more importantly, lack the nuclear envelope and epigenetic alterations normally associated with premature aging. Upon differentiation of HGPS-iPSCs, progerin and its aging-associated phenotypic consequences are restored. Specifically, directed differentiation of HGPS-iPSCs to SMCs leads to the appearance of premature senescence phenotypes associated with vascular aging. Additionally, our studies identify DNA-dependent protein kinase catalytic subunit (DNAPKcs) as a downstream target of progerin. The absence of nuclear DNAPK holoenzyme correlates with premature as well as physiological aging. Since progerin also accumulates during physiological aging6,12,13, our results provide an in vitro iPSC-based model to study the pathogenesis of human premature and physiological vascular aging. Three HGPS primary fibroblast lines, originally isolated from patients with the classical LMNA mutation (Gly608Gly), were transduced with retroviruses encoding OCT4, SOX2, KLF4, c-MYC, and GFP. Nanog-positive colonies were effectively obtained when using early passage, but not late passage (>25), HGPS fibroblasts (Fig. S1a). We focused on iPSC lines of a well characterized HGPS fibroblast line, AG019729–12. Compared to normal fibroblasts, HGPS fibroblasts (AG01972) showed abnormal nuclear morphology, reduced expression of the lamina components lamin B1 and LAP2β, loss of heterochromatin markers H3K9Me3, HP1α, and HDAC1, and reduced expression of nuclear proliferation marker Ki67 (Fig. 1a, S2). From HGPS fibroblasts, we derived six iPSC lines. In addition, we generated control iPSC lines from wild type fibroblasts (BJ and IMR-90 cell lines). Control and HGPS iPSC lines demonstrated pluripotent gene expression, demethylation of the OCT4 promoter and transgene silencing (Fig. 1b, S1, S3, S4a, and data not shown). They were maintained for more than 50 passages without a loss of pluripotency or the acquisition of detectable morphological or growth abnormalities. The pluripotency of each iPSC line was assessed by differentiation into the three embryonic germ layers in vitro, using embryoid body (EB) formation, and/or in vivo, by teratoma formation (Fig. S5a–d). Out of these lines, we primarily focused on HGPS-iPSC#4 and BJ-iPSC#3 for our studies (hereafter referred to as HGPS-iPSC or BJ-iPSC). Both BJ-iPSCs and HGPS-iPSCs were able to differentiate towards specialized mesoderm-derivatives such as smooth muscle cells (SMC), endothelial cells (Fig. S6a), or beating cardiomyocytes (Movie S1–S2). Moreover, all analyzed iPSC lines showed normal chromosomal integrity (Fig. S5e). Finally, LMNA sequencing confirmed the presence of the classical mutation in HGPS-iPSCs (Fig. S5f). Altogether, these data indicate that the somatic cells from HGPS patients, despite their significant premature senescence phenotypes and nuclear defects, have been properly reprogrammed and can be effectively maintained in a pluripotent state. Lamin A/C protein is expressed in differentiated somatic cells but is absent in embryonic stem cells (ESCs)11,14. Therefore, we next examined the expression of lamin A/C in the generated iPSC lines. As shown in Fig 2a, lamin A/C expression is significantly downregulated in iPSCs, compared to their parental fibroblasts, whereas lamin B1 transcripts were upregulated. Although progerin should follow a similar pattern of expression as observed for lamin A/C, LMNA expression is independent of promoter methylation status (Fig. S4b)15. Indeed, a complete loss of progerin mRNA in HGPS-iPSCs was observed (Fig. 2a). Furthermore, expression of lamin A/C and progerin proteins was practically undetectable (Fig. 2b, S4c). Since HGPS-iPSCs did not express progerin, we examined whether the nuclear abnormalities observed in HGPS fibroblasts would also be absent at the pluripotent stage. Our results indicate that all of the epigenetic, nuclear lamina and proliferation parameters analyzed in HGPS-iPSCs were indistinguishable from BJ-iPSCs (Fig. 2b–c, S3, S7). In addition, the nuclei of HGPS-iPSCs displayed the characteristic wrinkles and lobes observed in hESCs and iPSCs (Fig. S8), indicative of a reprogramming of the nuclear envelope components. Since the nuclear envelope associates with and regulates heterochromatin11,16, we next examined genome-wide CpG methylation in HGPS fibroblasts, BJ fibroblasts, HGPS-iPSCs, BJ-iPSCs, and H9 hESCs. Using bisulfite padlock probes and Illumina sequencing, we captured and quantified the methylation level of an average of 95,932 CpG sites within a set of 16,206 well annotated Differentially Methylated Regions (DMRs)17 per cell line (Table S1). The correlation coefficient of the global methylation levels between the pluripotent lines (BJ-iPSCs, HGPS-iPSCs and H9 hESCs) and the corresponding fibroblasts indicated that the generated pluripotent lines are much more closely related to each other and to hESCs than the two fibroblast lines (Fig. 2d). Interestingly, 586 autosome genes were found to be associated with regions that exhibited methylation differences between HGPS and BJ fibroblasts (Table S2, Fig S9a). Furthermore, based on DAVID18,19 analysis, we found that these genes were enriched for 21 Gene Ontology terms, most of which were related to development and transcriptional regulation (Fig S9a). In contrast, methylation differences between HGPS-iPSCs and BJ-iPSCs were only found for 33 autosome genes (Table S3), which showed no significant functional enrichment. Therefore, the presence of progerin in HGPS fibroblasts appears to lead to major epigenomic changes in various pathways. These changes were no longer present in HGPS-iPSCs, coinciding with the downregulation of progerin. Finally, genome-wide mRNA profiling demonstrated that HGPS-iPSCs and BJ-iPSCs are closely related together with H9 hESCs, and discrete from their parental fibroblasts (Fig. S9b–d). These results demonstrate the complete resetting of the nuclear architecture, epigenome and global gene expression in HGPS cells after being reprogrammed to pluripotency. To test whether the expression of progerin could be re-activated, we first subjected HGPS-iPSCs to in vitro differentiation via EB formation. Progerin mRNA was selectively induced in differentiated HGPS-iPSCs, but not in differentiated BJ-iPSCs (Fig. S10a). In contrast, lamin A was upregulated in both HGPS-iPSCs and BJ-iPSCs (Fig. S10a). This reversible suppression of progerin expression by reprogramming, and subsequent reactivation upon differentiation, provides a unique model system to study human premature aging pathologies. Progerin is known to accumulate mainly in arterial SMCs of HGPS patients, and vascular SMC degeneration is one of the characteristics of HGPS-associated arteriosclerosis6,7,20. In fact, vascular SMC senescence has been involved in the advanced arteriosclerosis of normal populations7,21,22. We therefore next asked whether SMCs differentiated from HGPS-iPSCs exhibit premature senescence phenotypes. Using a directed differentiation protocol, we obtained SMC populations from HGPS-iPSCs and BJ-iPSCs, the majority of which expressed characteristic SMC markers such as smooth muscle actin (SMA) and calponin (Fig. S6a). Immunoblotting and RT-PCR analyses confirmed the expression of progerin in HGPS-iPSC, but not BJ-iPSC-derived SMCs (hereafter referred to as “HGPS-SMC” and “BJ-SMC”, Fig. S6b–c). To model SMC senescence in vitro, the differentiated SMCs were serially passaged in culture. As shown in Fig. 3a–c and S10b, an increasing frequency of misshapen nuclei and a loss of the heterochromatin mark H3K9Me3 were specifically observed in HGPS-SMCs after serial passaging. HGPS-SMCs at later passages (i.e. passage 5) showed the typical characteristics of premature senescence, including increased senescence-associated-β-Gal (SA-β-Gal) staining (Fig. 3d–e, S10c), reduced telomere length (Fig. 3f), reduced number of Ki67-positive cells (Fig. 3g, S10d), and compromised cell proliferation (Fig. 3h, S10e). We also found a selective upregulation of senescence-related transcripts in HGPS-SMCs (Fig. S10f). To test whether the observed HGPS-related cell phenotypes were specific to SMCs, we differentiated HGPS-iPSCs into fibroblasts and measured progerin-associated parameters. Progerin expression in HGPS-iPSC-derived fibroblasts was detectable as early as passage 5 (Fig. S11a). However, we were unable to detect a loss of lamina or heterochromatin markers before passage 10 (Fig. S11b–c). Nonetheless, these defects were present specifically in HGPS-iPSC-derived fibroblasts, in contrast to control iPSC-derived fibroblasts analyzed at similar passage (data not shown). Thus, even though direct comparison of SMCs and fibroblasts is not possible due to their different culture conditions, our observations demonstrate that mesoderm lineages derived from HGPS-iPSCs display a characteristic HGPS phenotype. We next investigated whether progerin accumulation is the direct cause of the accelerated cell senescence observed in HGPS-SMCs. To this end, we induced ectopic expression of progerin in human primary vascular SMCs. We found that introduction of progerin in wild type SMCs resulted in compromised cell proliferation and nuclear defects, as we had observed in HGPS-SMCs (Fig. 3i, S12). As a complementary approach, we transduced HGPS-iPSCs with a lentiviral vector expressing a progerin-specific shRNA23. The modified iPSCs showed normal karyotypes as well as normal expression of lamina/epigenetic and pluripotent markers (Fig. S13a–b). After EB-based differentiation, both the mRNA and protein levels of progerin, but not those of lamin A, were substantially downregulated in the progerin-shRNA “corrected” HGPS-iPSCs compared to control cells (Fig. 3j, S13c–d). We next differentiated these “progerin-free” HGPS-iPSCs into SMCs (Fig. S14a). A dramatic improvement in the proliferation capability, as well as a downregulation of senescence-related transcripts, was found in the SMCs differentiated from the corrected HGPS-iPSCs (Fig. 3k and S14b–c). Furthermore, transduction of progerin shRNA into early passage HGPS-iPSC-derived fibroblasts resulted in a clear restoration of nuclear morphology and heterochromatin markers after extended culture (Fig. S15). Taken together, these data identify progerin as the key factor underlying the premature senescence phenotypes of HGPS-iPSC-derived cells. Since phenotypic characteristics of premature aging were able to be recapitulated by directed differentiation of the HGPS-iPSCs, we next investigated whether this model could serve to identify novel senescence-related markers. By using a sensitive MudPIT proteomic approach24,25, we identified DNA-dependent protein kinase catalytic subunit (DNAPKcs) as a hitherto unknown binding partner of progerin (Table S4). DNAPK holoenzyme, comprising of DNAPKcs and its regulatory subunits Ku70/Ku80, is involved in various aging-related cellular events26,27, and DNAPKcs or Ku70/Ku80-deficient mice exhibit accelerated aging27,28. To further confirm the association of progerin with DNAPKcs, we performed co-immunoprecipitation (co-IP) experiments. As shown in Fig 4a, ectopically expressed progerin associated tightly with endogenous DNAPKcs. In contrast, lamin A showed weak interaction with DNAPKcs, whereas both progerin and lamin A exhibited similar binding to lamin B1. Neither progerin nor lamin A co-immunoprecipitated with endogenous WRN protein. Since most of the nuclear proteins in complex with lamin A are destabilized in HGPS cells9,29, we analyzed the status of DNAPKcs in primary HGPS fibroblasts. We observed decreased nuclear DNAPKcs in HGPS fibroblasts when compared to normal fibroblasts (Fig. 4b–c). In addition, the regulatory subunits Ku70/Ku80 were also downregulated in HGPS fibroblasts (Fig. S16a). Interestingly, we detected a complete restoration of DNAPKcs/Ku70/Ku80 expression in HGPS-iPSCs (Fig. 4b, 4d, S3, S16b), although a deficiency in the expression of these proteins reappeared after differentiation into SMCs (Fig. 4e). These observations suggest that the downregulation of DNAPKcs in HGPS cells is dependent on the accumulation of progerin in differentiated cells. In fact, ectopic expression of progerin in primary vascular SMCs diminished DNAPKcs/Ku80 protein expression (Fig. 4f, S17). We next tested whether inactivation of DNAPKcs could partially contribute to some of the phenotypes observed in HGPS-SMCs. We found that knockdown of DNAPKcs reduced the proliferation of primary vascular SMCs (Fig. S18a). Finally, we extended our results and found that progressive loss of DNAPKcs/Ku70/Ku80 also occurs in fibroblasts isolated from normally aging individuals (Fig. S18b). Overall, our data suggest that deficiency of the DNAPK holoenzyme may constitute a novel marker for premature as well as physiological aging. In summary, our results not only highlight the plasticity of the lamina-epigenetics axis, but also point to the fact that the altered structure of the nuclear envelope, as well as the epigenetic modifications that accumulate during physiological aging12 or under specific disease conditions1,11, can be restored to normalcy by reprogramming (Fig. S19). The gradual onset and complexity of aging has impeded progress in understanding the pathogenesis of aging-related cardiovascular disorders. Recently, striking similarities between normal aging-associated and HGPS-associated arteriosclerosis have been reported6,16. Indeed, the levels of progerin increase gradually during physiological aging6. Our study provides the first evidence that, in a progerin-dependent manner, HGPS-iPSC-derived SMCs reach senescence-related phenotypes earlier than their normal counterparts. The iPSC-based accelerated aging model presented here and by Zhang et al30 may provide an avenue to model and study the pathogenesis of human aging-related vascular diseases as well as various human laminopathies1. METHODS SUMMARY iPSCs were generated from human fibroblasts with retroviruses encoding OCT4/SOX2/KLF4/c-MYC/GFP, and cultured on MEF feeder cells or Matrigel. SMCs were differentiated from iPSCs-derived CD34+ progenitor cells following an OP9-based protocol. ONLINE METHODS Cell culture H9 hESCs (WiCell Research) and iPSCs were maintained on a layer of mitotically inactivated mouse embryonic fibroblasts (MEFs) in hESC medium: DMEM/F12 (Invitrogen) supplemented with 0.1 mM non-essential amino acids (Invitrogen), 1 mM glutamax (Invitrogen), 20% Knockout Serum Replacement (Invitrogen), 55 μM β-mercaptoethanol (Invitrogen) and 10 ng/ml bFGF (Joint Protein hESCs and iPSCs were also cultured in Matrigel (BD Biosciences) with mTeSR medium (Stem Cell Technologies). Human HGPS fibroblasts AG01972, AG11498, AG06297, and normal fibroblasts GM00038 (9 year), AG05247 (87 year), and AG09602 (92 year) were purchased from Coriell Cell Repository. BJ normal human fibroblasts (CRL-2522) were purchased from ATCC. All human fibroblasts were cultured at 37°C in DMEM containing glutamax, non-essential amino acids, sodium pyruvate, and 15% fetal bovine serum (FBS). Human aortic smooth muscle cells were purchased from Lonza and maintained in SmGM-2 medium (Lonza, Cat. # CC-3182). Reagents Antibodies were obtained from the following sources. Abcam: anti-NANOG (ab21624), anti-H3K9Me3 (ab8898), anti-progerin (ab66587), anti-emerin (ab14208); anti-Ku70 (ab2172); Santa Cruz Biotechnology: anti-Oct-3/4 (sc-5279), anti-SOX2 (sc-17320), anti-HDAC1 (sc-7872), anti-DNAPKcs (sc-9051), anti-lamin A/C (sc-6215), anti-lamin A/C (sc-7293), anti-lamin B1 (sc-6217); Cell Signaling: anti-HP1α (2616); anti-Ku80 (2753); R&D systems: anti-Foxa2 (AF2400); Millipore: anti-TRA-1-60 (MAB4360) ; Sigma: anti-β-Tubulin III (T2200), anti-SMA(A5228), anti-Flag (M2), and anti-tubulin (T5168); Dako: anti-calponin (clone CALP); anti-endoglin (clone SN6h); BD Transduction Laboratories: anti-LAP2β (611000); MBL: Agarose-conjugated anti-GFP. Plasmids The pMXs vector containing the human cDNAs for OCT4, SOX2, KLF4 and c-MYC were purchased from Addgene (17217, 17218, 17219 and 17220, respectively). pBABE-puro-GFP-progerin and pBABE-puro-GFP-wt-lamin A were purchased from Addgene (17663 and 17662, respectively). Flag-progerin lentiviral vector was kindly provided by Dr. Lucio Comai 31. For the generation of the shRNA expression vectors against progerin and DNAPKcs, corresponding oligos (see Table S5) were cloned into a MluI/ClaI-cleaved pLVTHM plasmid (Addgene, 12247). All the constructs generated were subjected to DNA sequencing to confirm accurate shRNA target sequence. Retrovirus and lentivirus production For retrovirus production, 293T cells were transfected with the pMXs vectors carrying OCT4, SOX2, c-MYC, KLF4, or GFP cDNAs, together with the packaging plasmids (pCMV-gag-pol-PA and pCMV-VSVg, provided by Dr. Gerald Pao, The Salk Institute) using Lipofectamine 2000 (Invitrogen). Retroviruses were collected 36–48 h after transfection, and filtered through a 0.45 μM filter. Lentiviruses were generated by co-transfecting the pLVTHM vector together with the packaging plasmids (psPAX2 and pMD2.G, from Addgene, 12260 and 12259 respectively) into 293T cells using Lipofectamine 2000 (Invitrogen). Lentiviruses were collected 36 hours after transfection and concentrated by ultracentrifugation. iPSCs Generation For the generation of human iPSCs, human fibroblasts were seeded in a 6-well plate and spin-infected with a mix of high-quality retroviruses encoding OCT4, SOX2, KLF4, c-MYC, and GFP in the presence of 4 μg/ml polybrene. Three infections on consecutive days were performed. Six days after the first infection, fibroblasts were gently individualized with TrypLE (Invitrogen) and seeded onto fresh MEFs in the fibroblast culture medium. After 24 h, the medium was switched to hESC medium, and changed every 1–2 days depending on cell density. To establish the iPSC lines, colonies were manually picked and transferred onto MEF feeder cells for several passages before being transferred to Matrigel/mTesR conditions. Lentiviral infection of iPSCs HGPS-iPSC#4 cell line cultured on Matrigel was treated with 10 μM ROCK inhibitor Y-27632 for 1 h and then individualized with TrypLE. Cells were infected in suspension with either the concentrated lentivirus pLVTHM or pLVTHM-shRNA-Progerin in the presence of ROCK inhibitor and polybrene (4 μg/ml) for 1 h. Cells were centrifuged to remove the lentivirus and seeded back on fresh feeder MEFs in hESC media containing ROCK inhibitor. After being cultured for a few days, small colonies were manually passaged as a pool of colonies onto fresh MEFs to establish new iPSC lines. GFP expression was used as an indicator to determine successful integration of the lentiviruses. Cell differentiation For embryoid bodies (EBs) based differentiation, the iPSC colonies growing on MEFs were detached with dispase treatment, resuspended in DMEM/F12 medium supplemented with 0.1 mM non-essential amino acids, 0.5 mM L-glutamine, 10% FBS (Atlanta Biologicals), and 55 μM β-mercaptoethanol and cultured in low attachment 6-well plates for 4 days. The EBs were then plated on gelatin-coated plates and maintained for another 10–17 days. Differentiation of iPSCs into fibroblasts was performed as previously described32. Directed differentiation toward smooth muscle cells (SMCs) was performed essentially as previously described32 with slight modifications. Irritated OP9 cells were plated at 1 × 105 cells/well onto gelatinized 6-well plates in OP9 growth medium. After the formation of confluent iPS cell cultures for 4 and 5 days, undifferentiated iPS cells were harvested by treatment with 1 mg/mL dispase and dispersed by scraping to maintain the cells in small clumps. Concurrently, iPS cultures growing under the same conditions were used to obtain single cell suspension for counting. The iPSCs were added to OP9 cultures at a density of 3 × 105/2 mL per well of a 6-well plate in half TesR medium and half hESC media. iPSCs were allowed to recover for 1–2 days in hESC media. At day 0 of differentiation, the media was changed to Knockout DMEM supplemented with 10% FBS (HyClone), 10 mM β-mercaptoethanol, 1 mM L-glutamine, and 100 mM nonessential amino acids. The iPSC/OP9 cocultures were incubated for up to 10 days at 37°C in 5% CO2 conditions with medium change every other day. After 10 days of differentiation, the coculture cells were harvested with TrypLE (Invitrogen) for single-cell suspension and labeled with CD34 microbeads kit (Miltenyi Biotech, Cat. #130-046-702). Following the manufacturer's protocol, cells were passed through MS separation column attached to a Midi-MACS separation unit (Miltenyi Biotech) to obtain a magnet-retained fraction of purified CD34+ cells. Isolated CD34+ cells were then plated in smooth muscle cell media (SmGM-2 BulletKit, Lonza, Cat. # CC-3182) and maintained at 37°C in 5% CO2 conditions with medium change every 2–3 days34. SMCs were passaged using TrypLE (diluted 1:4) for 3 minutes at 37°C. To analyze early onset of senescence, cells were passaged at a ratio of 1:3 (~6000–7500 cells/cm2) only when the cells reached confluence. To calculate population doublings, SMCs seeded at 3500 cells/cm2 were passaged once culture reached 85–90% confluence. Cell growth was measured at every passage by calculation of accumulated population doublings using the formula (logH -logS) / log2.0 (H=number of cells harvested; S=number of cells seeded on the first day of each passage). Protein and mRNA analysis Cells were lysed and subjected to immunoblotting analysis according to the previously described method35. Total RNA was extracted using Trizol (Invitrogen) followed by cDNA synthesis using High capability RNA-to-cDNA Mater Mix (Invitrogen). Quantitative RT-PCR was performed using SYBR Green PCR Master Mix (Applied Biosystems). Primer sequences are listed in Table S5. Immunofluorescence microscopy Cells were fixed with 4% formaldehyde in PBS at room temperature (RT) for 20–30 min. After fixation, cells were treated with 0.4% Triton X-100 in PBS for 5 min at RT. After blocked with 10% FBS in PBS for 30 min, cells were incubated at RT for 1 h or at 4°C overnight with the primary antibody, followed by washing in PBS and incubation at RT for 1 h with the corresponding secondary antibody. Nuclei were stained with Hoechst 33342 (Invitrogen). Quantitative microscopy measurements were carried out as described previously9. Error bars represent standard deviations. Immunohistochemical detection of NANOG Cells were fixed with 4% formaldehyde in PBS at RT for 30 min, and permeabilized with 0.4% Triton-X100 in PBS for 10 min. Then the cells were incubated overnight with rabbit anti-human NANOG antibody in 1% BSA/PBS, followed by incubation with a secondary biotin-conjugated anti-rabbit antibody for 2 hours. Finally, cells were incubated with streptavidin-HRP for 1 hour (Vector), and NANOG-positive cells were visualized with a DAB substrate kit (Vector). Teratoma analysis To test pluripotency in vivo, NOD-SCID IL2Rgammanull mice (Jackson laboratories) were injected with the indicated iPSC lines and teratoma formation assessed. Briefly, ~106 iPSCs in ~50uL of hESC medium were injected into the testis or kidney capsule of anesthetized mice. Mice were monitored for teratoma formation and euthanized ~6–12 weeks after injection. Teratomas were harvested, processed and analyzed by hematoxylin-eosin staining and immunostaining. All animal experiments were performed with approval of The Salk Institute Institutional Animal Care and Use Committee (IACUC). Mutation validation Primer sequences to amplify exon 11 of the LMNA gene are listed in Table S5. 50 μl PCR reactions using 3 ng genomic DNA templates, 100 nM of the forward and reverse primers with 25 μl Taq 2× Master Mix (NEB) was performed at 94°C for 2 min, 34 cycles of 94°C 30 s, 55.5°C for 40 s, and 72°C for 40 s, and finally 72°C for 3 min. Products were purified with 0.9× volume of AMPure beads (Agencourt). Amplicons were sequenced by capillary Sanger sequencing (Genewiz). Results were visualized using an ABI Sequence Scanner. Genome–wide DNA methylation analysis Genomic DNA was extracted using ALLPrep DNA/RNA Mini kit (Qiagen). Bisulfite conversion and capture reaction was carried out on each sample (genomic DNA of fibroblasts, iPSCs, or hESCs). The detailed protocol for genomic DNA methylation has been described previously36, and the detailed information for DNA methylation is presented in Table S1. Bisufite sequencing of OCT4 and LMNA promoters Bisulfite conversion was carried out using 2 μg of purified genomic DNA using the Zymo EZ-DNA Methylation Gold Kit (Zymo Research) following the manufacturer's instructions. PCR was set up using previously published primers15. Cycling was terminated at 35 cycles. PCR products were purified using 2 % Size-Select E-gel (Invitrogen) and reamplified for 10 cycles using Phusion HF enzyme (NEB). PCR products were cloned using Zero-blunt PCR Cloning kit (Invitrogen) and heat transfected to TOP10 E. coli competent cells (Invitrogen). Individual colonies were selected and sent for single pass sequencing. DNA microarray and Bioinformatics analysis The GeneChip microarray processing was performed by the Functional Genomica Core in the Institute for Research in Biomedicine (Barcelona, Spain) according to the manufacturer's protocols (Affymetrix, Santa Clara, CA). The amplification and labeling were processed as indicated in Nugen protocol with 25ng starting RNA. For each sample, 3.75μg ssDNA were labeled and hybridized to the Affymetrix HG-U133 Plus 2.0 chips. Expression signals were scanned on an Affymetrix GeneChip Scanner (7G upgrade). The data extraction was done by the Affymetrix GCOS software v.1.4. The statistical analysis of the data was performed using ArrayStar 3. Briefly, raw CEL files were imported together with gene annotation from NetAffix (from 11/13/2009) and after checking for top replication quality for each of the 5 pairs of samples (R2>0.99), data was summarized at the gene level (20,765 genes) and the median was used for each gene and sample type. As both H9 hESCs and HGPS-iPSCs originate from female samples, and in order to remove any possible bias introduced by the X and Y chromosome-coded genes, we performed the same analysis with only autosome genes (19,884 genes). The result of the hierarchical clustering is very similar to the one using all genes and is shown in Figure 2f. In addition, a principal component analysis was performed on RMA-normalized probeset intensity values for autosomes using the prcomp function in R (http://www.r-project.org/) (the same figure including all genes gave highly similar results, data not shown). A figure illustrating the two first principal components is shown in figure S9c. Differences between some of the samples is shown using scatter plot of RMA-normalized intensity values in figure S9b. Multidimensional Protein Identification Technology (MudPIT) analysis of progerin-associated proteins The immunoprecipitation for MudPIT assay was performed as previously described24,25. In brief, HEK293T cells were transfected with GFP-progerin or GFP and maintained in culture for 48 h. After cells were lysed, the GFP-progerin, GFP, and their associated proteins were immunoadsorbed to anti-GFP agarose. The immunoprecipitates were then eluted with 8 M urea in 100 mM Tris, pH 8.5. The samples were reduced by adding 0.3 μL of 1M TCEP (for a final concentration of 5 mM TCEP) and incubated at RT. To alkylate, 1.2 μL of Iodoacetamide (10 mM final concentration) was added and the samples were subsequently incubated at RT in the dark for 15 minutes. The addition of 180 μL of 100 mM Tris pH 8.5 diluted the solutions to 2 M Urea. Calcium chloride (100 mM) was then added (2.4 μL) for a final concentration of 1 mM CaCl2. Trypsin (0.5 μg/μL) was added in the amount of 7.0 μL. The resulting mixtures were then shaken for 18 hours and incubated in the dark at 37 °C. To neutralize 13.5 μL of Formic Acid (90%) was added for a final concentration of 5% Formic Acid. The tubes were centrifuged for 30 minutes at 2 °C in a table-top centrifuge. Upon completion of the digestion, the proteins were pressure-loaded onto a fused silica capillary desalting column containing 3 cm of 5-μm strong cation exchange (SCX) followed by 3 cm of 5-μm C18 (reverse phase or RP material) packed into an undeactivated 250-μm i.d capillary. Using 1.5 mL of buffer A (95% water, 5% acetonitrile, and 0.1% formic acid) the desalting columns were washed overnight. Following the desalting process, a 100-μm i.d capillary consisting of a 10-μm laser pulled tip packed with 10 cm 3-μm Aqua C18 material (Phenomenex, Ventura, CA) was attached to the filter union (desalting column-filter union-analytical column) and the entire split-column (desalting column-filter union-analytical column) was placed in line with an Agilent 1100 quaternary HPLC (Palo Alto, CA) and analyzed using a modified 6-step separation, described previously25. The buffer solutions used were 5% acetonitrile/0.1% formic acid (buffer A), 80% acetonitrile/0.1% formic acid (buffer B), and 500 mM ammonium acetate/5% acetonitrile/0.1% formic acid (buffer C). Step 1 consisted of a 90 min gradient from 0–100% buffer B. Steps 2–5 had the following profile: 3 min of 100% buffer A, 2 min of X% buffer C, a 10 min gradient from 0–15% buffer B, and a 97 min gradient from 15–45% buffer B. The 2 min buffer C percentages (X) were 20, 40, 60, 80% respectively for the 6-step analysis. In the final step, the gradient contained: 3 min of 100% buffer A, 20 min of 100% buffer C, a 10 min gradient from 0–15% buffer B, and a 107 min gradient from 15–70% buffer B. As peptides eluted from the microcapillary column, they were electrosprayed directly into an LTQ 2-dimensional ion trap mass spectrometer (ThermoFinnigan, Palo Alto, CA) with the application of a distal 2.4 kV spray voltage. A cycle of one full-scan mass spectrum (400–1400 m/z) followed by 8 data-dependent MS/MS spectra at a 35% normalized collision energy was repeated continuously throughout each step of the multidimensional separation. Application of mass spectrometer scan functions and HPLC solvent gradients were controlled by the Xcalibur datasystem. As each step was executed, its spectra were recorded to a RAW file. This data was then converted into .ms2 format through the use of RawXtract (Version 1.9). From the .ms2 files, poor quality spectra were removed from the dataset using an automated spectral quality assessment algorithm37. MS/MS spectra remaining after filtering were searched with the SEQUEST™ algorithm38 against the NCBI RefSeq Human (04-23-2010) protein database concatenated to a decoy database in which the sequence for each entry in the original database was reversed25,39. All searches were parallelized and performed on a Beowulf computer cluster consisting of 100 1.2 GHz Athlon CPUs40. No enzyme specificity was considered for any search. SEQUEST results were assembled and filtered using the DTASelect (version 2.0) program. DTASelect 2.0 uses a linear discriminant analysis to dynamically set XCorr and DeltaCN thresholds for the entire dataset to achieve a user-specified false positive rate. The false positive rates are estimated by the program from the number and quality of spectral matches to the decoy database. The hits detected uniquely in the GFP-progerin sample but not in GFP sample represent proteins that are specifically associated with progerin, by either direct or indirect interactions. Co-Immunoprecipitation BJ human fibroblasts were transduced with retrovirus encoding GFP-progerin, GFP-lamin A or GFP, and maintained in culture for 72h. For immunoprecipitation, cells were lysed in ice-cold lysis buffer (250 mM NaCl, 0.5% Triton X-100, 50 mM Tris, pH 7.5, 1 mM EGTA, 1 mM EDTA, 10% glycerol, and complete protease inhibitor cocktail (Roche Diagnostics)). Samples were briefly sonicated and immunoprecipitated by incubating with anti-GFP agarose. The immunoprecipitates were washed extensively in lysis buffer, eluted in SDS sample buffer, and subjected to immunoblotting. Senescence-associated beta-galactosidase (SA-βgal) assay SA-βgal assay were performed based as previously described methods41. Measurement of telomere length Genomic DNA was isolated from 1 × 106 cells. The telomere-specific oligonucleotide probe (5'-TTAGGGTTAGGGTTAGGGTTAGGG-3'; ValueGene) was end-labeled using γ-32P-ATP (MP Biomedicals) and T4 polynucleotide kinase (NEB). Two μg of genomic DNA for each sample was digested with AluI (NEB) and MboI (NEB) and subjected to Southern analysis with the telomere-specific probe. Mean telomere length was calculated from ΣODi/(ΣODi/ΣMWi). ODi and MWi are optical density and molecular weight at a given position i, respectively. Cell proliferation assay Cell proliferation was determined with CellTiter 96® AQueous One Solution Cell Proliferation Assay (MTS (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium)), according to the protocol provided by the manufacturer (Promega). Statistical analysis Results are presented as mean±s.d. Comparisons were performed with student's t-test or one-way anova. p<0.05 was defined as statistically significant. Supplementary Material 1 2 5 6 7 8 9
Author and article information
Journal
Title:
Annual Review of Physiology
Abbreviated Title:
Annu. Rev. Physiol.
Publisher:
Annual Reviews
ISSN
(Print):
0066-4278
ISSN
(Electronic):
1545-1585
Publication date Created:
February
10 2018
Publication date
(Print):
February
10 2018
Volume: 80
Issue: 1
Pages: 27-48
Affiliations
Article
DOI: 10.1146/annurev-physiol-021317-121454
PubMed ID: 28934587
SO-VID: af7a62fb-f2f6-41c1-b9b4-0e0dccc32bee
Copyright © ©
2018
History
ScienceOpen disciplines: Medicine,Nutrition & Dietetics,Cardiovascular Medicine,Clinical Psychology & Psychiatry,Public health
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ScienceOpen disciplines: Medicine, Nutrition & Dietetics, Cardiovascular Medicine, Clinical Psychology & Psychiatry, Public health