Metabolic changes during cellular senescence investigated by proton NMR-spectroscopy

Mechanisms of Ageing and Development 134 (2013) 130–138

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Metabolic changes during cellular senescence investigated by proton NMR-spectroscopy Claudia Gey a, Karsten Seeger b,* a b

Institute of Biology and Institute of Physiology, University of Lu¨beck, 23538 Lu¨beck, Germany Institute of Chemistry, University of Lu¨beck, 23538 Lu¨beck, Germany

A R T I C L E I N F O

A B S T R A C T

Article history: Received 9 October 2012 Received in revised form 10 December 2012 Accepted 2 February 2013 Available online 13 February 2013

Cellular senescence is of growing interest due to its role in tumour suppression and its contribution to organismic ageing. This cellular state can be reached by replicative loss of telomeres or certain stresses in cell culture and is characterized by the termination of cell division; however, the cells remain metabolically active. To identify metabolites that are characteristic for senescent cells, extracts of human embryonic lung fibroblast (WI-38 cell line) have been investigated with NMR spectroscopy. Three different types of senescence have been characterized: replicative senescence, DNA damage-induced senescence (etoposide treatment) and oncogene-induced senescence (hyperactive RAF kinase). The metabolite pattern allows (I) discrimination of senescent and control cells and (II) discrimination of the three senescence types. Senescent cells show an increased ratio of glycerophosphocholine to phosphocholine independent from the type of senescence. The increase in glycerophosphocholine implicates a key role of phospholipid metabolism in cellular senescence. The observed changes in the choline metabolism are diametrically opposite to the well-known changes in choline metabolism of tumour cells. As tumours responding to chemotherapeutic agents show a ‘‘glycerophosphocholine-tophosphocholine switch’’ i.e. an increase in glycerophosphocholine, our metabolic data suggests that these malignant cells enter a senescent state emphasizing the role of senescence in tumour suppression. ß 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords: Metabolism Cellular senescence 1 H NMR spectroscopy Glycerophosphocholine

1. Introduction Cellular senescence has attracted much attention in the last years due its role in tumour suppression (Campisi and d’Adda di Fagagna, 2007). In 1961, Hayflick and Moorhead observed that cells divide only a finite number of times in culture (Hayflick, 1965; Hayflick and Moorhead, 1961). This phenomenon is known as the Hayflick limit and is caused by the replicative loss of telomeres. Also certain stresses are capable of inducing senescence and that seems to be telomere-associated as well (Hewitt et al., 2012; Suram et al., 2012). Senescent cells are still metabolically active, but cannot reenter the cell cycle after stimulation with mitogens. A proteome

Abbreviations: hTERT, human telomerase reverse transcriptase; GFP, green fluorescent protein; PDL, population doubling level; 4-HT, 4-hydroxytamoxifen; ER, estrogen receptor; SA-b-gal, senescence-associated b-galactosidase; SAHF, senescence-associated heterochromatic foci; GPC, L-a-glycerophosphocholine; PC, phosphocholine; HIF-1a, hypoxia inducible factor 1a; PCA, principal component analysis. * Corresponding author. Tel.: +49 451 500 4298; fax: +49 451 500 4241. E-mail addresses: [email protected] (C. Gey), [email protected] (K. Seeger). 0047-6374/$ – see front matter ß 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.mad.2013.02.002

analysis of dermal fibroblasts from human donors identified proteins that undergo changes during ageing (Boraldi et al., 2003). Trougakos et al. (2006) identified proteins belonging to e.g. the cytoskeleton and energy production that have a different expression profile in young WI-38 cells compared to replicative senescent cells. This raises the question of whether cells also undergo metabolic changes. There are few studies addressing metabolism in cellular senescence. Early reports showed an increased glycolysis (Bittles and Harper, 1984; Goldstein et al., 1982) in senescent skin and lung fibroblasts and an unchanged ATP/ADP ratio (Goldstein et al., 1982) in senescent skin fibroblasts. However, the ATP turnover in human diploid skin fibroblasts decreases throughout the live span of cells (Muggleton-Harris and Defuria, 1985). Recently, the importance of lipid metabolism in cellular senescence has been highlighted (Ford, 2010). Since e.g. diacylglycerol or phosphatidic acid are important second messengers, alterations in the lipid metabolism have a direct impact on signalling pathways. Senescent WI-38 cells failed to form diacylglycerol after serum stimulation due to a failure of phospholipase D activation (Venable et al., 1994). Moreover, phospholipase D dysfunction was related to ceramide signalling (Venable et al., 1994), i.e. senescence was accompanied by elevated

C. Gey, K. Seeger / Mechanisms of Ageing and Development 134 (2013) 130–138

levels of ceramide and an increased neutral sphingomyelinase activity in WI-38 cells (Venable et al., 1995, 2006). Additionally, there is less formation of monounsaturated fatty acids and reduced formation of phospholipids in human skin fibroblasts (Maeda et al., 2009). Changes in the lipid metabolism, especially the choline metabolism, have attracted much attention in the field of malignant transformation of cells and treatment of tumours (Glunde et al., 2011). Despite the specific data available on changes in the energy situation and the lipid metabolism during cellular senescence, there is a basic knowledge gap on the overall metabolic state of senescent cells. Metabolic profiling of cells, tissues, or living systems has attracted much attention in the last years and has been shown to be very effective in characterizing certain cellular or physiological states (Coen et al., 2008; Lenz and Wilson, 2006). NMR spectroscopy or mass spectrometry combined with statistical analysis allows identification of differences between individual groups. NMR spectroscopy has been shown to be extremely powerful for metabolite analysis due to simple sample preparation, no requirement for pre-selection or modification of metabolites and a non-destructive analysis. Metabolite analysis can be performed with whole cells, cell extracts, body fluids or tissues. There exists a multitude of studies that investigated the e.g. tumour metabolism (Iorio et al., 2005; Mirbahai et al., 2011; Pan et al., 2011), autoimmune diseases (Seeger, 2009) or even the whole organism ageing in a senescence accelerated mouse strain (Jiang et al., 2008). The present study aims at the characterization of metabolism in senescent cells and the respective controls. Three different triggers of senescence, namely replicative, DNA damage and oncogeneinduced senescence have been investigated in human diploid fibroblasts (WI-38). High resolution NMR spectroscopy was employed to analyse cellular extracts with regard to their metabolite composition. Differences in the metabolite profile of young and senescent cells could be linked to lipid metabolism. Our study provides a better understanding of how senescence and malignant transformation might interplay at the level of cellular (lipid) metabolism. 2. Materials and methods

131

2.1.3. DNA damage-induced senescence The WI-38 hTERT/GFP-RAF1-ER cell line was also used to induce senescence by DNA damage. For that purpose cells were treated with 20 mg/ml etoposide (Sigma E1383, stock solution in DMSO, final concentration of DMSO was 0.05% (v/v)) for 5 days. 72 h before harvest ethanol was added to the medium (final concentration as for 4-HT treated cells). As a control for DNA damage-induced senescence WI-38 hTERT/GFP-RAF1-ER cells were incubated with ethanol and DMSO. The WI-38 hTERT/GFP-RAF1-ER cells were cultured in a 5% carbon dioxide and 3% oxygen incubator. Cells that have been used for investigating the effect of immortalization and the different oxygen environments (3% and 21%) were grown in the absence of ethanol. All WI-38 fibroblasts were grown in modified Eagle’s medium + 10% fetal bovine serum + 1 mM sodium pyruvate + 2 mM L-glutamine + 0.1 mM MEM non-essential amino acids (life technologies, Gibco, Darmstadt, Germany). PDL was calculated as follows: final PDL number at the end of a given subculture = 3.32 (log cell yield at harvest  log cell number used as inoculum) + doubling level of the inoculum (McAteer and Davis, 1998). 2.1.4. Effect of 4-hydroxytamoxifen on lipid metabolism In the oncogene-induced senescence pathway overexpression of RAF is controlled by an estrogen receptor and induced by addition of 4-hydroxytamoxifen (4-HT) to the culture medium. WI-38 fibroblasts do respond to a number of steroids like estrogen that causes a reduced life span and a reduced cell density if permanently present in the medium at 5 mg/ml (Kondo et al., 1983). As induction of senescence is achieved within 72 h and 4-HT is present at much lower concentrations we exclude these effects in our study. 4-HT is a derivative of tamoxifen that is used as anti-estrogen drug in treatment of different cancers. Tamoxifen was found to have estrogen receptor-independent effects by activation of phospholipases C and D in human mammary fibroblast (Cabot et al., 1997). Precisely, 15 mM 4-HT showed a very slight increase in phospholipase D activity compared to the control (Cabot et al., 1997). Yet, the amounts of 4-HT used in our experiments are much lower and we therefore expect no significant influence on the metabolism caused by 4-HT activation of phospholipases C and D. Another effect of tamoxifen is the inhibition of the ceramide glycosylation in cancer cells (Lavie et al., 1997) resulting in increased ceramide levels. Accumulation of ceramide also accompanies cellular senescence yet due to increased hydrolysis of membrane sphingomyelin by elevated neutral sphingomyelinase activity (Venable et al., 1995, 2006). If 4-HT acts in a similar way, i.e. increasing the ceramide levels, this would potentiate the senescent state and not contradict the obtained data. 2.1.5. Effect of etoposide on lipid metabolism Etoposide is an anti-tumour drug that acts via induction of DNA damages (Kaufmann, 1998; Robles et al., 1999). Also for etoposide treatment it has been shown that ceramide accumulates in human leukemia cells (Perry et al., 2000). As mentioned for 4-HT, this increase in ceramide is a stress response and would potentiate the senescent state. An overview of the experimental approach is illustrated in Fig. 1.

2.1. Cell lines and culture 2.1.1. Replicative senescence Unmodified WI-38 fibroblasts of high population doubling level (PDL), i.e. PDL 34, were obtained from the Coriell Institute for Medical Research/Cell Repositories (Camden, US) and grown in a 5% carbon dioxide and 21% oxygen incubator until entering replicative senescence that is reached earlier under these conditions. Cells were senescent at PDL 55–60 and then used for NMR experiments. Young WI38 cells of PDL 22 (American Type Culture Collection-LGC Standards, Wesel, Germany) have been cultured, harvested at PDL 28 and then used for the NMR experiments. These cells were considered as pre-senescent/young cells and used as a control for replicative senescence. To have identical cultivation conditions as for oncogene-induced senescence, 72 h before harvest ethanol was added to the medium (0.01% (v/v) final concentration as for 4-hydroxytamoxifen treated cells, vide infra). 2.1.2. Oncogene-induced senescence The WI-38 hTERT/GFP-RAF1-ER cell line was developed as described in (Jeanblanc et al., 2012) and used to induce senescence by conditional activation of the RAF1 kinase. Briefly, WI-38 human embryonic fibroblasts (American Type Culture Collection-LGC Standards, Molsheim, France) were first immortalized with hTERT and subsequently nucleofected with pWZL3-Blast-GFP-DRAF1-DD:ER DNA. Stably integrated clones were selected for resistance to G418 and blasticidin, respectively. Senescence-inducible clones were obtained by screening for homogeneous senescence after addition of 4-hydroxytamoxifen (4-HT, Sigma H6278; 20 nM 4-HT final concentration) for 3 days. 4-HT was added to media from a stock solution in ethanol. Final concentration of ethanol was 0.01% (v/v). Ethanol was added to non-induced WI-38 hTERT/GFP-RAF1-ER cells yielding a final concentration of 0.01% (v/v) as control for oncogene-induced senescence. The WI-38 hTERT/GFP-RAF1-ER cells were cultured in a 5% carbon dioxide and 3% oxygen incubator.

2.2. Staining for senescence-associated b-galactosidase Histochemical detection of senescence-associated b-galactosidase (SA-b-gal) at pH 6 was used as a marker for senescence (Dimri et al., 1995). Fixed cells were washed with PBS containing 1 mM MgCl2 and incubated with staining solution (1 mg/ml X-Gal + 5 mM K3Fe(CN)6 + 5 mM K4Fe(CN)6 + 150 mM NaCl + 2 mM MgCl2 in citric acid/sodium phosphate buffer pH 6) over night at 37 8C in ambient atmosphere. For visualization of senescence-associated heterochromatic foci (SAHFs) cell nuclei were stained with DAPI (1 mg/ml, 10 min at room temperature). 2.3. Sample preparation for NMR-measurements Cells of two confluent Petri dishes (10 cm diameter) have been pooled for NMR analysis. Typically, a confluent Petri dish contains approximately 3–4  106 cells. In case of replicative senescence cells are less dense (a Petri dish contains approximately 106 cells) and three Petri dishes have been combined. In total, 3

control cells

native WI-38 (PDL 28) (EtOH)

senescent cells

replicative senescence native WI-38 (PDL 55-60)

immortalized WI-38 (stable transfected with hTERT/GFP-RAF1-ER) 4-HT (EtOH)

etoposide (EtOH, DMSO)

oncogene induced DNA damage induced senescence senescence

Fig. 1. Investigated triggers of senescence and experimental design.

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samples of replicative senescent cells and 6 samples of each other group have been obtained and used for NMR analysis. Cell extracts were obtained by a methanol/ chloroform extraction as described in Lee et al. (2009). Briefly, the cell pellets were resuspended in a 2:1 mixture of chloroform/methanol and mixed. After sonification (3 times, 3 s intervals, mixing in between) at the highest setting using a Sonifier Bandelin HD 200 equipped with a MS72 tip, 900 ml of chloroform saturated water was added and the solution was centrifuged at 16,000  g for 20 min at 4 8C. The upper aqueous phase was lyophilized and stored at 80 8C. Shortly before the NMRmeasurements cell extracts have been dissolved in 110 ml NMR buffer and were transferred to a 3 mm Shigemi tube. 3 mm Shigemi tubes have been used to obtain good signal to noise ratios also for low abundant metabolites. The NMR buffer consists of 0.1 M sodium phosphate buffer with 0.1 mM TSP-d4 and 0.02% sodium acid added. The pH of the buffer was adjusted to 7 in water before lyophilisation and dissolving in D2O. 2.4. NMR-measurements of cell extracts NMR measurements have been performed on a Bruker Avance 500 equipped with a TCI cryo probe at 298 K system temperature. Despite using D2O as solvent, the residual water signal is still very intense in the spectra. Therefore water suppression was applied by using the standard Bruker pulse sequence noesypr1d with a relaxation delay (d1) of 3 s for magnetization recovery after each transient, 0.1 s mixing time, 64 k data points and 512 transients. In this pulse sequence saturation of the water signal is performed during the relaxation delay and the mixing time that results in improved water suppression compared to pulse sequences using only presaturation. Furthermore, it enables evaluation of signals close to the suppressed water signal whereas methods based on excitation sculpting can affect the signal intensity of nearby signals. The spectra were processed with Topspin 2.0 with no zero filling and an exponential line broadening factor of 0.7 Hz was applied prior the Fourier transformation. The spectra have been manually phased, base line corrected and referenced via the TSP-d4 main signal at 0 ppm. 2.5. Principal component analysis Statistical analysis of the spectra was performed with the statistics tool of Amix 3.9.1. (Bruker). The spectra were binned into 0.01 ppm buckets between 10 ppm and 0.2 ppm by excluding the water region (4.5–5 ppm) and the DMSO signal (2.76– 2.70 ppm). The buckets have been scaled to total intensity to account for different

sample concentrations. Different sample concentration can arise due to different cell numbers during cell culture; due to different cell volumes because senescent cells and control cells show different morphologies but also due to slightly different sample volumes caused by the use of 3 mm Shigemi tubes. For PCA analysis small variances (5%) have been suppressed. For comparison of the senescent cells and controls of one senescence trigger the minimum variance level was set to 10%. Buckets that contribute to discrimination have been subjected to a two-sided Student’s t-test and obtained p-values have been corrected for multiple testing (Bonferroni correction). Metabolites have been identified by reference spectra of the pure substances. The NMR spectra have been recorded in the same buffer under similar acquisition conditions with a typical concentration of 20 mM.

3. Results Cell extracts of senescent and control cells have been investigated with NMR spectroscopy to identify metabolite pattern that can be related to the senescent state. We characterized three different triggers of senescence – replicative, DNA damageinduced and oncogene-induced senescence (Fig. 1). The WI-38 fibroblast cell line was the first cell line used to describe replicative senescence. Subsequently, these cells have been used to study senescence induced by other stresses and therefore most experimental data on senescence is available for this cell line. 3.1. Induction of cellular senescence All three investigated senescence triggers result in a senescent state as shown by the occurrence of different senescence markers (Fig. 2). The WI-38 hTERT/GFP-RAF1-ER cell line was developed by Jeanblanc et al. (2012) to easily study oncogene-induced senescence and to narrow senescence pathways by eliminating effects associated with telomere loss. Activation of the GFP-RAF-ER

Fig. 2. Occurence of senescence markers in WI-38 fibroblasts for different types of senescence. (a) Senescence associated b-galactosidase staining was found in 42% of replicative senescent cells (PDL 55–60). Oncogene-induced senescence in WI-38 hTERT/GFP-RAF1-ER cells resulted in 43% b-gal positive cells after treatment with 20 nM 4HT for 72 h. Senescence caused by DNA damage was induced in WI-38 hTERT/GFP-RAF1-ER cells by treating with 20 mg/ml etoposide for 5 days and lead to a positive staining reaction in 71% of cells. Control were normal, proliferating WI-38 fibroblasts of PDL 28 with 11% cells positive for SA-b-gal. (b) DAPI staining of nuclei shows the presence of senescent-associated heterochromatic foci for more than 94% of the counted nuclei in replicative and oncogene-induced senescence and 50% in etoposide-induced senescence. Less than 7% of the nuclei of proliferating cells showed some fragmentation.

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construct by addition of 4-HT leads to a stable induction of senescence (Jeanblanc et al., 2012). Morphological changes, positive staining for senescence-associated b-galactosidase (SAb-gal) in 43% of the cells and heterochromatic foci in more than 94% of the counted nuclei have been observed after addition of 4HT as described in the literature proving successful induction of cellular senescence. TERT-immortalized cells have been used for DNA-damage induced senescence as shown in (Zhang et al., 2003). As a model for DNA-damaged induced senescence we used the WI-38 hTERT/GFPRAF1-ER cells and treated them with etoposide, a drug that triggers senescence by inducing the formation of DNA double-strand breaks (Robles et al., 1999). The use of immortalized cells impedes artefacts due to different PDLs as young and senescent WI-38 fibroblasts activate different pathways upon etoposide treatment (Seluanov et al., 2001). Etoposide treated cells are positive for the investigated senescence markers with a positive SA-b-gal staining in 71% of the cells and 50% of SAHF positive nuclei. Normal WI-38 fibroblasts of high PDL were kept in culture until no population doubling was detected at least during two cell passages. The calculated PDL was then in the range of 55–60 and the majority of cells stained positive for SA-b-gal (42%) and heterochromatic foci (94%). 3.2. Influence of immortalization and culture conditions on the metabolic pattern of WI-38 cells Although the same cell type was used in the study, some experimental aspects might affect the metabolism of the cells. DNA

damage-induced senescence and oncogene-induced senescence have been studied in hTERT immortalized and GFP-RAF-ER transfected cells grown under conditions closer to physiological values i.e. 3% oxygen. NMR spectra of extracts of these cells show indeed differences compared to untransfected WI-38 cells grown in a 21% oxygen atmosphere. These are mainly activated sugars (UDP-Glc and UDP-GlcNAc, Supplemental Fig. A1), phosphocholine, phosphocreatine, glutamine and glutamate (Supplemental Table A1). These substances show increased levels in native WI-38 cells. Also ethanol as well as DMSO influence metabolism of cells (data not shown). For that reason only differences between the senescent cells and the control cells with the corresponding solvent will be discussed. 3.3. Senescent and control cells have different metabolic profiles Measuring proton NMR spectra of senescent and control cells enables determination of differences between the two states. A typical 1D proton NMR spectrum of cell extracts from oncogeneinduced senescent cells and respective control cells are shown in Fig. 3. Representative NMR spectra of each senescence trigger and the respective control are shown in Supplemental Fig. A2. A principal component analysis (PCA) demonstrates that senescent cells are different from control cells (Fig. 4). Discrimination of both groups can be achieved by a combination of principal component 1 and 2. In case of oncogene-induced senescence the control group and the senescent cells separate from the two other groups. The metabolite pattern of the three HDO

PC

Tyr

amino acids, sugar moieties

UDP-GlcNAc

NAD+

UDP-GlcNAc

formate

GPC

a

133

Gln Glu Glu Ac Gln PCr Cr

anomeric sugar protons

Lac

Ala

Leu Val Ile

*

controll cells

b

sencescent cells

9

8

7

6

5

4

3

2

1

H ppm

Fig. 3. Representative 500 MHz proton spectra of cell extracts from control cells (a) and oncogene-induced senescent cells (b). Representative spectra of the other two investigated senescence triggers are provided in the supplementary information. Isolated signals of major metabolites and metabolites of interest are highlighted (HDO suppressed water signal, Cr creatine, PCr phosphocreatine, GPC L-a-glycerophosphocholine, PC phosphocholine, Ac acetate, Lac lactate, amino acids according to their three letter code).

C. Gey, K. Seeger / Mechanisms of Ageing and Development 134 (2013) 130–138

134

0.4 0.3

0.1 0 -0.1 -0.2

principal component 2

0.2

-0.3

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

-0.4 0.8

principal component 1 Fig. 4. Principal component analysis (PCA) of senescent cells and controls. Both groups can be clearly discriminated by a combination of principal component 1 and 2. Filled symbols ( , , ) represent senescent cells, whereas control cells are denoted by signs ( , , ).Oncogene-induced senescence( ) is separate from replicative ( ) and DNA damage-induced senescence ( ). For the control cells the native WI-38 fibroblasts ( ) and the control for DNA damage-induced senescence ( ) are different than the control for oncogene induced senescence ( ). Two outlier spectra that show poor water suppression and intense signals at 3.56–3.74 ppm, respectively have been excluded from PCA.

investigated senescence types could be differentiated by PCA as well, allowing the discrimination of replicative, DNA damageinduced and oncogene-induced senescence (Supplemental Fig. A5). To identify differences in the metabolic pattern of each senescence trigger the senescent cells and controls cells have been subjected to an individual PCA (Supplemental Fig. A4). In all three senescence triggers control cells and senescent cells are discriminated by principal component 1 (Supplemental Fig. A4). Buckets and corresponding metabolites that contribute to principal component 1 are given in Table 1. Quantification of metabolic changes would be questionable due to the morphological changes that accompany the senescent state and therefore only changes in metabolite signals are reported. Replicative senescence is mainly marked by an increase of L-a-glycerophosphocholine (GPC), ()inosine, glutamine and leucine. Whereas UDP-GlcNAc, ADP + ATP, glutamate, phosphocreatine, phosphocholine (PC), and some unknown resonances (0.935 ppm, 2.395 ppm, 3.855 ppm and 5.915 ppm) are decreased in senescent cells. Lactate and acetate show a trend to lower levels in senescent cells. Senescence induced by overexpression of the oncogene RAF is characterized by elevated levels of GPC, an N-acetylated compound (2.025 ppm, Supplemental Fig. A3) and unknown signals at 3.485– 3.925 ppm compared to the control cells. A decrease of the signals corresponding to lactate and glutamate can be observed. The metabolites acetate, phosphocreatine and PC show a trend for lower levels. In the third investigated senescence type, the etoposide induced senescence, only GPC and two buckets (0.955 and 0.965) are elevated. Three metabolites (lactate, acetate and PC) are decreased in the senescent cells. In addition the buckets at 1.225 and 1.255 ppm also show a significant decrease. 3.4. Changes in acetate and GPC are a common feature in senescence Besides the clear differences in the metabolite pattern of the three types of senescence, there are few metabolites that show the same changes independent from the induction of senescence. Acetate and lactate are always decreased in senescence. Also PC

appears always at lower levels in senescent cells and GPC is the only metabolite that is always increased (Fig. 5). The change in GPC level seems not to be a continuous process. Native WI-38 fibroblasts at PDL 50 (data not shown) that are considered to be (pre)senescent do not show the characteristic increase in GPC as seen for senescent cells at PDL 55–60 but still display a GPC to PC ratio comparable to young immortalized WI-38 fibroblasts. 4. Discussion Analysis of metabolite profiles delivers valuable data on the current situation in biological systems. NMR spectroscopy has been shown to be very suitable for establishing metabolite profiles and has been extensively applied in this field. There already exists a multitude of metabolic data on malignant transformation of cells. However, there is only little information about metabolic changes in cellular senescence. With regard to the fact that senescence is considered to be an important mechanism of tumour suppression, the aim of this study was to establish metabolic profiles of young and senescent cells. These profiles could be put into relation with metabolic data from malignant transformation. Three different triggers of senescence – replicative, DNA damage-induced and oncogene-induced senescence have been investigated in human diploid fibroblast (WI-38) according to their effect on cellular metabolism. Cell extracts of senescent and young cells have been investigated with NMR spectroscopy to identify metabolite pattern that can be related to the senescent state. It would be tempting to quantify these changes however, senescent WI-38 fibroblasts show an increased cell volume compared to young cells and with large variations (Mitsui and Schneider, 1976). It seems that the cell size and the life span of cells are directly related (Yang et al., 2011). Therefore, changes in the total amount of a metabolite would not necessarily translate into different intracellular metabolite concentrations. Normalization to the total metabolite content seems to be more appropriate to identify changes in metabolite concentrations. 4.1. Effect of immortalization and/or the oxygen conditions on cellular metabolism hTERT immortalized WI-38 cells have been grown at 3% oxygen. These cells show decreased levels of activated sugars. Activated sugars are substrates for glycosyl transferases that glycosylate proteins and lipids. O-GlcNAcylation, besides phosphorylation, is one key mechanism for the regulation of cellular signalling and has implications in cell viability, cell growth (Butkinaree et al., 2010; Hu et al., 2010) and response to stresses (Zachara et al., 2004). Fibroblasts that lose the ability to O-GlcNAcylate proteins fail to induce the expression of the transcription factors c-Fos, c-Jun and c-Myc after serum stimulation and arrest growth (O’Donnell et al., 2004). Therefore, changes in the concentration of free UDP-GlcNAc as seen in this study might translate into changes of glycosylation pattern of proteins and hence be an effect of the immortalization by hTERT transfection. This is supported by a study of cis-platin responding brain tumour cells that show increased levels in UDPGlcNAc accompanying the onset of cell death (Pan et al., 2011). However, cell death per se seems not to come along with increased levels of UDP-GlcNAc. A study of human colon cancer cells identified that these cells show increased levels of UDP-GlcNAc and UDP-GalNAc under conditions that prevent differentiation of the cells (Wice et al., 1985). Low oxygen concentrations, often designated as hypoxia in literature, can also affect the metabolism. This is reflected in WI-38 cells by changes in enzyme activity related to oxidative stress (Balin et al., 2010) and higher growth rates at 5% oxygen (Balin

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135

Table 1 Major metabolites that are altered in senescent cells compared to control cells (" and # indicate an increase or decrease of the signal in the NMR spectra of the cell extracts of senescent cells compared to control cells). p-Values according to a Student’s t-test have been corrected for multiple testing (Bonferroni). The original p-values are given in brackets. Metabolite

Replicative senescencea

Oncogene-induced senescenceb

Etoposide-induced senescencec

Lactate

1.335 ppm # n.s. (0.036) 0.955 ppm " 5.30  104 (7.26  106) 0.975 ppm " 3.31  103(4.53  105) 2.375 ppm # 9.65  103 (1.32  104) 2.455 ppm " 1.76  102 (2.40  104) 3.235 ppm" 6.36  105 (8.72  107) 3.225 ppm # 5.14  104 (7.03  106) 1.925 ppm # n.s. (0.047) –

1.335 ppm # 8.28  104 (1.24  105) n.s.

1.335 ppm # 6.75  103 (3.75  104) 0.955 ppm " 6.22  105 (3.46  106) –

Ile/Leu/unknown Leu Glu Gln GPC Phosphocholine (PC) Acetate Unknown N-Ac resonance at 2.030 ppm UDP-GlcNAc ADP/ATP ()inosine phosphocreatine unknown

7.975 ppm # 8.35  104 (1.14  105) 8.545 ppm # 2.94  103 (4.03*105) 8.245 ppm " 4.43  105 (6.07  107) 3.045 ppm # n.s. (4.36  103) 0.935 ppm (Ile, unknown) " 6.59  103 (9.03  105) 0.945 (Ile, unknown) " 8.08  103 (1.11  104) 2.395 ppm # 4.60  102 (6.31  104) 3.855 ppm " 8.15  103 (1.12  104) 3.905 ppm (GPC) " 3.63  104 (4.97  106) 5.915 ppm " 4.77  104 (6.54  106)

–d 2.335 ppm # 9.39  104 (1.40  105) –

n.s. –

3.235 ppm " 2.36  105 (3.52  107) 3.225 ppm # n.s. (0.018) 1.915 ppm # n.s. (0.05) 2.025 ppm " 6.70  103 (1  104) –

3.235 ppm " 7.17  105 (3.99  106) 3.225 ppm # 6.08  106 (3.38  107) 1.915 ppm # 2.73  105 (1.52  106) –

–

–

–

–

3.045 ppm # n.s. (8.80  104) 1.235 ppm # 1.80  102 (2.68  104) 3.485–3.535 ppm " 3.39  103 (5.06  105)e 3.575–3.595 ppm " 4.18  103 (6.24  105)f 3.835 ppm " 0.014 (2.12*104) 3.905–3.925 (GPC) " 2.73  104 (4.08  106)g

–

–

0.965 ppm (unknown, Ile, Leu) " 1.94  105 (1.08  106) 1.225 ppm # 2.63  103 (1.46  104) 1.255 ppm # 8.04  105 (4.47  106) 3.905 ppm (GPC) " 1.28  105 (7.12  107)

Abbreviations: n.s. non significant. a 73 buckets have been obtained from PC1. b 67 buckets have been obtained from PC1. c 18 buckets have been obtained from PC1. d bucket does not contribute to PC 1. e 3.515 ppm. f 3.595 ppm. g 3.925 ppm.

et al., 1976). In addition, low oxygen concentrations induce the hypoxia inducible factor 1a (HIF-1a) that has also been shown for WI-38 fibroblasts (Poulios et al., 2006). HIF-1a regulates gene expression to adapt for hypoxia. Changes in the glucose metabolism induced by hypoxia (via HIF) also affect activated sugars as e.g. UDP-GlcNAc as recently reviewed (Shirato et al., 2011). For myeloma cells it was reported that UDP-GlcNAc and UDP-GalNAc are increased under hypoxic conditions (Lodi et al., 2011). Thus, changes in activated sugars can be observed between immortalized WI-38 cells grown in a hypoxic environment and native WI-38 cells grown under normoxic conditions. These changes can probably be translated into changes of protein glycosylation. 4.2. Metabolic profiles of different senescence triggers Our results show that senescent cells and control cells indeed possess different metabolic profiles. In addition, also the different triggers of senescence can be distinguished. Cristofalo and Kritchevsky (1966) found that respiration and glycolysis in WI-38 did not undergo any significant changes upon cultivation. They also observed that levels of endogenous lactate do

not alter significantly with increasing proliferation. Two other studies found an increase in glycolysis. Goldstein et al. (1982) investigated human skin fibroblasts. Bittles and Harper (1984) had the same observation in human embryonic lung fibroblast but a different strain than the WI-38 cells. Thus different cell types might be the cause of the observed differences. In our study lactate and acetate are decreased in senescent WI38 cells independent of the trigger. This indicates decreased glycolysis and might reflect a change of metabolic pathways to generate energy. For immortalized cells this might also be a consequence of the immortalization. The increase in GPC levels and the decrease in PC levels is also a common feature of all three senescence types implicating changes in the phospholipid metabolism during cellular senescence (vide infra). Despite these metabolic similarities, the three investigated senescence types can be distinguished according to their metabolic profile as shown by PCA (Supplemental Fig. A5). Thus the observed changes in the metabolic pattern can attribute solely to the senescent state of the cells while in parallel some differences are related to the triggers that induced the senescent state. DNAdamage induced senescence exhibit differences in metabolites that

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replicative GPC PC

choline

etoposide-induced

oncogene-induced

GPC PC

GPC PC

choline

choline

senescent cells

control cells 3.250

3.225

1

H ppm

3.250

3.225

1

H ppm

3.250

3.225

1

H ppm

Fig. 5. Expanded 500 MHz NMR spectra of cell extracts from senescent cells and control cells. The spectra are scaled to total intensity and only the region with the signals of the total choline containing compounds is shown. For each group spectra of six extracts (replicative senescent cells 3 extracts) have been superimposed. The PDLs of the replicative senescent cells are 55–60. The PDL of the young cells (control for replicative senescence) is 28.

are common to all three triggers. The changes in oncogene-induced senescence point toward an increased energy demand in senescent cells. These senescent cells show a reduced level of phosphocreatine – a metabolite that is used to restore ATP in cells. In a very recent study Quijano et al. (2012) identified an increased fatty acid oxidation in oncogene (Ras) induced senescence of IMR-90 cells. This finding is pointing to an increased energy demand and shows that metabolic differences between different triggers of senescence exist. Replicative senescence shows most differences, with changes e.g. in UDP-GlcNAc that can be linked to glycosylation or changes in phosphocreatine that are related to the energy metabolism. 4.3. GPC to PC ratio as a marker of senescence A common characteristic of all three investigated senescence types is the increase of the GPC signal and the decrease of PC levels (Fig. 5). This points toward an implication of the phospholipid metabolism in cellular senescence (Fig. 6). Alterations of phospholipid metabolism play a pivotal role in tumour progression. During malignant transformation of cells a ‘‘GPC to PC’’ switch is observed, implying an increase of PC compared to GPC (Aboagye and Bhujwalla, 1999; Iorio et al., 2005). This is related to an increased phosphatidylcholine catabolism and choline uptake from the medium into the cell (reviewed in (Glunde et al., 2011)) caused by higher activities of phospholipase C/D and choline kinase. As we observe an increase in GPC levels during senescence this must be related to another pathway of phosphatidylcholine breakdown than in tumour cells namely by action of phospholipase A1 and/or A2 and lysophospholipase (Fig. 6). This is consistent with an impairment of the phospholipase D/diacylglycerol pathway observed in senescent WI-38 cells (Venable et al., 1994, 1995) and with findings that secretory phospholipase A2 can induce cellular senescence in human dermal fibroblasts (Kim et al., 2009). Furthermore, induction of cell cycle arrest and apoptosis by phenylbutyrate in human prostate cancer (Milkevitch et al., 2005) or by cis-platin in rat glioma cells (Mirbahai et al., 2011) also

increases the GPC levels. One study examined the effect of immortalization and transformation of Schwann cells. It was found that GPC increases when these cells stopped growing due to expression of the H-ras oncogene (Bhakoo et al., 1996). These studies did not investigate markers for senescence but it is likely that these treatments also cause a senescence like phenotype (Chang et al., 1999). Wang et al. (1998) showed that nasopharyngeal carcinoma cells display features of senescence after cis-platin treatment, however changes in glycerophosphocholine have not been analysed. In general, it would be interesting to determine senescence markers and metabolic changes in tumours responding to chemotherapeutic agents. The different enzyme activities that are found in tumour cells and senescent cells are also mirrored in the metabolic profile of

tumour progression

plD

medium

choline

ck

plC

PC

phosphaditylcholine plA

pde

GPC

lpl

lysolecithin

senescence Fig. 6. Schematic representation of the choline metabolism. Tumour progression is characterized by an increased uptake of choline from medium and an increased catabolism of phosphatidylcholine to phosphocholine and choline. Choline is phosphorylated by the choline kinase (ck) that also shows an increased activity in tumour cells. Increased levels of GPC account for an increased activity of the phospholipase A (plA) pathway and can be related to cellular senescence. Abbreviations: plC phospholipase C: plD phospholipase D: lpl lysosphospholipase, pde glycerophosphocholine phosphodiesterase.

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these cells. If the alterations in the phospholipid metabolism are cause or effect cannot be derived, however, lipid metabolism seems to be a key player in cellular transformations (Ford, 2010). Interventional studies like modulation of phospholipase activity will help to understand in more detail the shift in phospholipid metabolism during cellular senescence and will further improve our understanding of cellular senescence. 5. Concluding remarks High resolution NMR spectroscopy has been used to establish metabolic profiles of senescent WI-38 human fibroblasts. Cell extracts of replicative, DNA damage-induced (etoposide treatment) and oncogene-induced (overexpression of RAF) senescent cells have been investigated. The metabolic profiles allow discrimination of the different senescent types, however, all in common is the increase in GPC implicating a key role of the phospholipid metabolism in cellular senescence. Elevated levels of GPC reflect the catabolism of phospholipids via phospholipase A1 and/or A2 and lysophospholipase and are contrary to pathways that are activated in malignant transformation namely phospholipases C and D. Therefore elevated levels of GPC might provide a metabolic marker for cellular senescence. Acknowledgements CG and KS thank the DFG Cluster of Excellence ‘‘Inflammation at Interfaces’’ (EXC 306/1) for financial support. Carl Mann is acknowledged for access to the WI-38 hTERT/GFP-RAF1-ER cells and critical reading of the manuscript. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.mad.2013.02.002. References Aboagye, E.O., Bhujwalla, Z.M., 1999. Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Research 59, 80–84. Balin, A., Reimer, R., Reenstra, W., Lilie, S., Leong, I., Sullivan, K., Allen, R., 2010. Effects of oxygen, growth state, and senescence on the antioxidant responses of WI-38 fibroblasts. AGE 32, 435–449. Balin, A.K., Goodman, D.B.P., Rasmussen, H., Cristofalo, V.J., 1976. The effect of oxygen tension on the growth and metabolism of WI-38 cells. Journal of Cellular Physiology 89, 235–249. Bhakoo, K.K., Williams, S.R., Florian, C.L., Land, H., Noble, M.D., 1996. Immortalization and transformation are associated with specific alterations in choline metabolism. Cancer Research 56, 4630–4635. Bittles, A.H., Harper, N., 1984. Increased glycolysis in ageing cultured human diploid fibroblasts. Bioscience Reports 4, 751–756. Boraldi, F., Bini, L., Liberatori, S., Armini, A., Pallini, V., Tiozzo, R., Pasquali-Ronchetti, I., Quaglino, D., 2003. Proteome analysis of dermal fibroblasts cultured in vitro from human healthy subjects of different ages. Proteomics 3, 917–929. Butkinaree, C., Park, K., Hart, G.W., 2010. O-linked beta-N-acetylglucosamine (OGlcNAc): extensive crosstalk with phosphorylation to regulate signaling and transcription in response to nutrients and stress. Biochimica et Biophysica Acta 1800, 96–106. Cabot, M.C., Zhang, Z.-c., Cao, H.-t., Lavie, Y., Giuliano, A.E., Han, T.-Y., Jones, R.C., 1997. Tamoxifen activates cellular phopholipase C and D and elicits protein kinase C translocation. International Journal of Cancer 70, 567–574. Campisi, J., d’Adda di Fagagna, F., 2007. Cellular senescence: when bad things happen to good cells. Nature Reviews Molecular Cell Biology 8, 729–740. Chang, B.-D., Broude, E.V., Dokmanovic, M., Zhu, H., Ruth, A., Xuan, Y., Kandel, E.S., Lausch, E., Christov, K., Roninson, I.B., 1999. A senescence-like phenotype distinguishes tumor cells that undergo terminal proliferation arrest after exposure to anticancer agents. Cancer Research 59, 3761–3767. Coen, M., Holmes, E., Lindon, J.C., Nicholson, J.K., 2008. NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology. Chemical Research in Toxicology 21, 9–27. Cristofalo, V.J., Kritchevsky, D., 1966. Respiration and glycolysis in the human diploid cell strain wi-38. Journal of Cellular Physiology 67, 125–132.

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