Metabolomics

, Volume 10, Issue 2, pp 270–279 | Cite as

Metabolomic profiling of sodium fluoride-induced cytotoxicity in an oral squamous cell carcinoma cell line

  • Hiroshi Sakagami
  • Masahiro Sugimoto
  • Shoji Tanaka
  • Hiromi Onuma
  • Sana Ota
  • Miku Kaneko
  • Tomoyoshi Soga
  • Masaru Tomita
Original Article

Abstract

Sodium fluoride (NaF) is used in dentistry as a preventive agent for dental caries because of its ability to remineralize the tooth surface and its antibacterial effect. Although one of its target molecules in bacteria is enolase, its site of action in human cells has not been identified. The aim of this study was to identify target metabolites that are coupled to NaF-induced cytotoxicity in the HSC-2 human oral squamous cell carcinoma cell line. Cell viability, membrane integrity and apoptosis induction were analyzed by MTT assay, trypan blue exclusion and caspase-3 activation, respectively. Cells were treated with a minimal cytotoxic concentration of NaF for various times and subjected to comprehensive metabolomics analysis using capillary electrophoresis-mass spectrometry. In the early stages, inhibition of the enolase reaction in glycolysis pathway was observed. This was coupled with rapid inhibition of the progression of TCA cycle. In the later stages, gradual increases in the AMP/ATP ratio (a putative marker of apoptosis) and oxidized products (e.g. GSSH, and methionine sulfoxide), and marginal changes in polyamine levels (putative marker of necrosis) were observed. This manuscript provides the new insight into the global impact of NaF on metabolic pathways in human oral squamous cell carcinoma cells.

Keywords

Fluoride Apoptotic cell death Oral squamous cell carcinoma Capillary electrophoresis time-of-flight-mass spectrometry 

1 Introduction

Fluoride (NaF), which is used in dentistry as a preventive agent for dental caries, inhibits the demineralization and promotes the remineralization of the tooth surface (Arnold et al. 2007; Jimenez-Farfan et al. 2011; Ten Cate 2012; Vale et al. 2011), and exerts antibacterial activity against oral bacteria (Shashikiran et al. 2006). Therefore, this compound has been used topically (Ijaz et al. 2010) and in the fluoridation of drinking water (McDonagh et al. 2000). However, high concentrations of fluoride are known to induce acute or chronic toxicities such as dental fluorosis (DenBesten and Thariani 1992; Gessner et al. 1994), skeletal fluorosis (Wang et al. 1994) and renal toxicity (Willinger et al. 1995). Fluoride induces the disruption of the actin cytoskeleton (Li et al. 2005), endoplasmic reticulum stress in ameloblast-derived cells (Kubota et al. 2005; Sharma et al. 2008), and necrosis in thymocytes (Matsui et al. 2007), and induces apoptosis in epithelial lung cells (Thrane et al. 2001), osteoblasts (Yan et al. 2009), odontoblasts (Karube et al. 2009), renal epithelial cells (Murao et al. 2000), human promyelocytic leukemia (HL-60) (Otsuki et al. 2011) and the human oral squamous cell carcinoma (OSCC) cell line, HSC-2 (Otsuki et al. 2011). We have recently reported that high concentrations of NaF induce apoptotic markers such as caspase-3 activation and internucleosomal DNA fragmentation in HSC-2 cells, but not in human gingival fibroblasts (HGF) (Otsuki et al. 2011). Although many compounds induce a common apoptotic phenotype, their biological mechanisms may differ.

One of the molecular targets of fluoride is the glycolytic enzyme, enolase (also named 2-phospho-d-glycerate hydro-lyase; IUBMB enzyme nomenclature, EC 4.2.1.11), which catalyses the conversion of 2-phospho-d-glycerate (2PG) (enolase substrate) to phosphoenolpyruvate (PEP). NaF has been reported to competitively inhibit enolase in an in vitro assay system (Guha-Chowdhury et al. 1997; Kaufmann and Bartholmes 1992), in bacterial cells (Hata et al. 1990), and in supragingival plaques (Takahashi and Washio 2011). We have previously reported that NaF inhibits glucose consumption in HL-60 cells (Otsuki et al. 2005), while our preliminary study using a fluoride-specific electrode demonstrated that only 0.01–0.09 % of the initially added NaF was recovered from HSC-2 cells (Acra et al. 2012). However, to our knowledge, the global impact of fluoride on metabolic pathways in oral cells has not been investigated previously.

Metabolomics is a new omics technology that enables cellular functions to be analyzed via a holistic view of metabolic pathways. Of several metabolite measurement techniques, capillary electrophoresis time-of-flight-mass spectrometry (CE-TOF-MS) suits the simultaneous profiling of energy metabolic pathways, e.g., glycolysis, tricarboxylic acid (TCA), amino acid and nucleotide pathways (Soga et al. 2006).

The aim of this study was to determine whether NaF inhibits enolase activity in HSC-2 cells, and if so, whether increased amounts of TCA cycle metabolites are produced in compensation. We have recently reported that ATP utilization (measured by the AMP/ATP ratio) decreased while oxidative stress (measured by the GSSH/GSH ratio, methionine sulfoxide/methionine ratio, and cysteine-glutathione disulphide) and polyamine levels increased during the eugenol-induced necrotic cell death of HSC-2 cells (Koh et al. 2013). Therefore, we investigated whether NaF, which induces apoptosis, induces similar or different expression patterns of these markers, by performing comprehensive metabolomics analysis using CE-TOF-MS.

2 Materials and methods

2.1 Materials

The following materials were obtained from the indicated suppliers: Dulbecco’s modified Eagle’s medium (DMEM; GIBCO BRL, Grand Island, NY, USA); fetal bovine serum (FBS; JRH Bioscience, Lenexa, KS, USA); NaF (Wako Pure Chem. Ind., Ltd., Osaka, Japan); 3-(4,5-dimethyl-thiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT; Sigma-Aldrich, St. Louis, MO, USA); 6- and 96-well plastic culture dishes and plates (Becton–Dickinson, Franklin Lakes, NJ, USA).

2.2 Cell culture

Human OSCC cells (HSC-2; obtained from Riken Cell Bank, Tsukuba, Japan) were cultured at 37 °C in DMEM supplemented with 10 % heat-inactivated FBS in a humidified 5 % CO2 atmosphere. The cells were detached with 0.25 % trypsin in phosphate-buffered saline without magnesium and calcium (PBS(−)) and either subcultured or used for experiments.

2.3 Cell viability assays

Two assays were used to measure cell viability. First, the MTT assay was used to evaluate cell growth potential based on mitochondrial activity. Cells (3 × 103) were seeded in 96-well plates and incubated for 48 h. Near-confluent cells were treated with NaF in fresh culture medium for the indicated times in triplicate or quintuplicate. After removing the culture medium, MTT (0.2 mg/ml) was added to each well and incubation was continued for 4 h at 37 °C. After removal of the medium, the formazan product was dissolved with DMSO (100 μl) and the absorbance at 540 nm was determined using a micro plate reader (Biochromatic Labsystem, Helsinki, Finland) (Otsuki et al. 2011). Second, membrane intactness was evaluated using the trypan blue exclusion test. The intact cells that excluded the 0.15 % trypan blue were judged to have maintained membrane integrity, whereas the damaged cells that incorporated trypan blue were judged to have lost membrane integrity.

2.4 Assay for caspase activation

Cells (6 × 104) were seeded in six-well plates and incubated for 48 h. Near-confluent cells were treated with NaF in fresh culture medium for the indicated times in triplicate. Cells were lysed in lysis and reaction buffer (50 mM Tris–HCl, pH 7.5, 0.3 % Nonidet P-40 (NP-40), and 1 mM DTT). After standing for 10 min on ice and centrifugation for 10 min at 10,000×g, the supernatant was collected. The lysate (50 μl, equivalent to 100 μg protein) was mixed with 50 μl of lysis and reaction buffer containing substrate for caspase-3 (DEVD-pNA (p-nitroanilide)). After incubation for 4 h at 37 °C, the liberated pNA was measured using a microplate reader at 405 nm (Otsuki et al. 2011).

2.5 Assay for metabolic profiling

Cells (6 × 105) were seeded in 10-cm dishes (Becton–Dickinson Labware, NJ, USA) and incubated for 48 h. The medium was replaced with fresh medium and the cells were incubated for 30 min at 37 °C in a 5 % CO2 incubator to stabilize the pH and temperature of the culture medium. The cells were treated without (control) or with 8 mM NaF in fresh culture medium for various incubation times in triplicate. The cells were washed twice with 5 ml of ice-cold 5 % d-mannitol and then immersed for 10 min in 1 ml of methanol containing internal standards (25 μmol/l each of methionine sulfone, 2-[N-morpholino]-ethanesulfonic acid and d-camphor-10-sulfonic acid). The methanol extract (supernatant) was collected. To 400 μl of the dissolved samples, 400 μl of chloroform and 200 μl of Milli-Q water were added and the mixture was centrifuged at 10,000×g, for 3 min at 4 °C. The aqueous layer was filtered to remove large molecules by centrifugation through a 5-kDa cut-off filter (Millipore, Billerica, MA, USA) at 9,100×g for 3.5 h at 4 °C. The filtrate (320 μl) was concentrated by centrifugation and dissolved in 50 μl of Milli-Q water containing reference compounds (200 μmol/l each of 3-aminopyrrolidine and trimesate) immediately before CE-TOF-MS analysis.

To 100 μl of the medium samples, 400 μl of methanol containing internal standards (25 μmol/l each of methionine sulfone, 2-[N-morpholino]-ethanesulfonic acid and d-camphor-10-sulfonic acid) was added and mixed well. Subsequently, 500 μl of chloroform and 200 μl of Milli-Q water were added and the mixture was centrifuged at 10,000×g, for 3 min at 4 °C. The aqueous layer was filtered to remove large molecules by centrifugation through a 5-kDa cut-off filter (Millipore) at 9,100×g for 3.5 h at 4 °C. The filtrate (320 μl) was concentrated by centrifugation for 2 h at 40 °C and dissolved in 50 μl of Milli-Q water containing reference compounds (200 μmol/l each of 3-aminopyrrolidine and trimesate) immediately before CE-TOF-MS analysis. The medium were also treated for each time point in triplicate. The cells were analyzed independently two times (2× triplicate) while mediums were analyzed only one time (1 × triplicate).

2.6 CE-TOF-MS analysis

The instrumentation and measurement conditions used for CE-TOF-MS are described elsewhere (Soga et al. 2006; Sugimoto et al. 2012b). Briefly, cation analysis was performed using an Agilent CE capillary electrophoresis system, an Agilent G6220A LC/MSD TOF system, an Agilent 1100 series isocratic HPLC pump, a G1603A Agilent CE-MS adapter kit, and a G1607A Agilent CE-ESI-MS sprayer kit (Agilent Technologies, Waldbronn, Germany). Anion analysis was performed using an Agilent CE capillary electrophoresis system, an Agilent G6210A LC/MSD TOF system, an Agilent 1200 series isocratic HPLC pump, a G1603A Agilent CE-MS adapter kit, and a G1607A Agilent CE-electrospray ionization (ESI) source-MS sprayer kit (Agilent Technologies). For the cation and anion analyses, the CE-MS adapter kit included a capillary cassette that facilitates thermostatic control of the capillary. The CE-ESI-MS sprayer kit simplifies coupling of the CE system with the MS system and is equipped with an electrospray source. For system control and data acquisition, G2201AA Agilent ChemStation software for CE and Agilent MassHunter software for TOF-MS was used. The original Agilent SST316Ti stainless steel ESI needle was replaced with a passivated SST316Ti stainless steel and platinum needle (passivated with 1 % formic acid and a 20 % aqueous solution of isopropanol at 80 °C for 30 min) for anion analysis.

For cationic metabolite analysis using CE-TOF-MS, sample separation was performed in fused silica capillaries (50 μm i.d. × 100 cm total length) filled with 1 mol/l formic acid as the reference electrolyte. The capillary was flushed with formic acid (1 M) for 20 min before the first use and for 4 min before each sample injection. Sample solutions (3 nl) were injected at 50 mbar for 5 s and a voltage of 30 kV was applied. The capillary temperature was maintained at 20 °C and the temperature of the sample tray was kept below 5 °C. The sheath liquid, composed of methanol/water (50 % v/v) and 0.1 μmol/l hexakis(2,2-difluoroethoxy) phosphazene (Hexakis), was delivered at 10 μl/min. ESI-TOF-MS was conducted in the positive ion mode. The capillary voltage was set at 4 kV and the flow rate of nitrogen gas (heater temperature = 300 °C) was set at 7 psig. In TOF-MS, the fragmentor, skimmer and OCT RF voltages were 75, 50 and 125 V, respectively. Automatic recalibration of each acquired spectrum was performed using reference standards ([13C isotopic ion of protonated methanol dimer (2MeOH + H)]+, m/z 66.0632) and ([protonated Hexakis (M + H)]+, m/z 622.0290). Mass spectra were acquired at a rate of 1.5 cycles/s over a m/z range of 50–1,000.

For anionic metabolite analysis using CE-TOF-MS, a commercially available COSMO(+) capillary (50 μm i.d. × 102 cm, Nacalai Tesque, Kyoto, Japan), chemically coated with a cationic polymer, was used for separation. Ammonium acetate solution (50 mmol/l; pH 8.5) was used as the electrolyte for separation. Before the first use, the new capillary was flushed successively with the running electrolyte (pH 8.5), 50 mmol/l acetic acid (pH 3.4), and then the electrolyte again for 10 min each. Before each injection, the capillary was equilibrated for 2 min by flushing with 50 mM acetic acid (pH 3.4) and then with the running electrolyte for 5 min. A sample solution (30 nl) was injected at 50 mbar for 30 s, and a voltage of −30 kV was applied. The capillary temperature was maintained at 20 °C and the sample tray was cooled below 5 °C. An Agilent 1100 series pump equipped with a 1:100 splitter was used to deliver 10 μl/min of 5 mM ammonium acetate in 50 % (v/v) methanol/water, containing 0.1 μM Hexakis, to the CE interface. Here, it was used as a sheath liquid surrounding the CE capillary to provide a stable electrical connection between the tip of the capillary and the grounded electrospray needle. ESI-TOF-MS was conducted in the negative ionization mode at a capillary voltage of 3.5 kV. For TOF-MS, the fragmentor, skimmer and OCT RF voltages were set at 100, 50 and 200 V, respectively. The flow rate of the drying nitrogen gas (heater temperature = 300 °C) was maintained at 7 psig. Automatic recalibration of each acquired spectrum was performed using reference standards ([13C isotopic ion of deprotonated acetic acid dimer (2 CH3COOH–H)], m/z 120.03841), and ([Hexakis+deprotonated acetic acid (M + CH3COOH–H)], m/z 680.03554). Exact mass data were acquired at a rate of 1.5 spectra/s over a m/z range of 50–1,000.

2.7 Analysis of metabolomic data

2.7.1 Data analysis and statistical analysis

Raw data were analyzed using our proprietary software, MasterHands (Sugimoto et al. 2010), which follows typical data processing flows, including the detection of all possible peaks, elimination of noise and redundant features, and generation of an aligned data matrix with annotated metabolite identities and relative areas (peak areas normalized to those of internal standards) (Sugimoto et al. 2012a). Concentrations were calculated using external standards based on relative area, i.e., the area divided by the area of the internal standards.

2.7.2 Heatmap and clustering

The amount of each metabolite was expressed as a molar concentration per one cell (amol/cell) (1 attomol = 10−18 mol). Only metabolites that were detected in more than 60 % of 16 samples (n ≥ 10) were used. The concentration of each metabolite was averaged from triplicate samples, converted by a factor of log 2 (to increase the color intensity contrast), and subtracted from the mean values calculated in all groups per metabolite to determine the color. The mean value was expressed by a white color. Clustering was performed by Pearson correlation.

2.8 Statistical analysis

Student’s t test (two-tailed) was used for statistical comparisons. P-values were collected by false discovery rate considering multiple significance tests in parallel across all metabolites. Data analyses and visualization were conducted using GraphPad Prism (ver. 5.04, Intuitive Software for Science, San Diego, CA, USA), and Mev TM4 software (ver. 4.8.1, Dana-Farber Cancer Institute, Boston, MA, USA) (Saeed et al. 2003).

3 Results

3.1 Kinetics of cytotoxicity induced by NaF

NaF inhibited the growth of HSC-2 cells in a dose-dependent manner. Significant growth inhibition was observed above 2 mM NaF (P < 0.05), and essentially all cells died after incubation for 24 h in 8 mM NaF (P < 0.0001) (Fig. 1a). In parallel with growth inhibition, a significant increase in caspase-3 activity was observed (Fig. 1a). Growth inhibition by NaF was also time-dependent. A small but significant decrease in the viable cell number was observed 2 h after treatment with 8 mM NaF (Fig. 1b), while membrane integrity remained at 100 % throughout the 3 h incubation with NaF (data not shown). Based on these data, HSC-2 cells were treated with 8 mM NaF (the minimum concentration that completely killed the cells) for various times up to 3 h, and changes in metabolites were profiled by metabolomics analysis.
Fig. 1

Kinetics of cytotoxicity induced by NaF in HSC-2 cells. a Dose–response. HSC-2 cells were incubated for 6 h (for caspase assays; n = 3) or 48 h (for MTT viability assays; n = 5) to determine caspase-3 activity and viable cell numbers. b Time courses. HSC-2 cells were incubated for the indicated times with 8 mM NaF and the viable cell number was determined by MTT assay (n = 3). Each value represents the mean ± SD of 3–5 samples. * and *** indicate P < 0.05 and P < 0.0001, respectively

3.2 Metabolomic profiling time-course

3.2.1 Overview of quantified metabolites

CE-TOF-MS analysis identified and quantified a total of 127 metabolites. Fold changes in metabolite concentrations relative to control (at 0 min) were visualized as a heat map (Fig. 2). As expected, the profiles at each time point were ordered according to the time transition, which indicated that the overall metabolomic change gradually increased with time. In addition, these profiles were separated into two clusters at early times (10–60 min) and late times (120–180 min), with a drastic change observed between 60 and 120 min. The time-course showed six clusters, labeled (A)–(F), of which clusters (A), (E) and (F) contained metabolites showing relatively large fold changes. In particular, clusters (E) and (F), which contained most of the amino acids, showed large increases at later times, while clusters (C) and (D) contained metabolites which decreased slightly, including the amino acids proline and glutamic acid.
Fig. 2

Heat map and bar graph visualization of the quantified metabolites. Heat map showing the quantified metabolites using a bluewhitered scheme, and fold-changes of metabolites in cells exposed to increasing concentrations of NaF on a log2 scale. Labels 10180 indicate the time (min) after NaF-treatment. Labels (AF) were assigned to the prominent clusters

3.2.2 Glycolytic pathway and tricarboxylic acid cycle

The time-courses for metabolites of the glycolytic pathway and tricarboxylic acid (TCA) cycle are shown in Fig. 3a, b, respectively. NaF treatment rapidly increased the intracellular concentration of fructose 1,6-phosphate, a metabolite at the first stage of glycolysis, followed by sustained increases in 3-phosphoglycerate (3PG), dihydroxyacetone phosphate (DHAP) and 2-phosphoglycerate (2PG), the latter of which is a substrate of enolase. In contrast, the intracellular concentrations of phosphoenolpyruvate (PEP), a product of enolase, and pyruvate, a product of glycolysis, were almost constant. Lactate, an end product of glycolysis, rapidly decreased within 30 min and subsequently remained almost constant. Taken together, these data indicated that NaF treatment inhibited the enolase reaction.
Fig. 3

Time courses of the concentrations of metabolites in the glycolysis pathway (a), TCA cycle (b), and NAD+, NADH, and their ratios (c). The error bars indicate the SD of triplicate samples. The SD less than the open circles radius for each time points were not shown

Intermediate metabolites of the TCA cycle showed two distinct time-course patterns (Fig. 3b). The first four metabolites of the TCA cycle, citrate, cis-aconitate, isocitrate and 2-oxoglutarate, showed a rapid increase within 30 min followed by a gradual decrease, possibly expending the acetyl-CoA produced by oxidative decarboxylation of pyruvate. Succinate showed a gradual increase. Neither time-course correlated positively with the time-course of acetyl-CoA. Although aconitase [EC 4.2.1.3], an enzyme that interconverts citrate and cis-aconitate, is inactivated by oxidative stress (Bulteau et al. 2003), these clusters suggest that the reactions involving succinate, succinyl-CoA and 2-oxoglutarate might be important factors for the response to NaF-treatment. Succinyl-CoA may inhibit citrate synthesis, thus inhibiting the progression of a second TCA cycle. The time-course for NAD+ and NADH (Fig. 3c) showed that NADH was significantly reduced by two-thirds after 30 min, possibly being utilized for ATP production necessary for apoptosis induction, while NAD+ decreased gradually. These data indicated that inhibition of glycolytic enolase did not induce the TCA cycle in cycle.

We independently conducted the same experiment to confirm these findings (Fig. S1). Although initial concentrations of several metabolites, such as G6P, were different, overall time-course patterns were similar except for acetyl-CoA. To quantitatively access the similarity of the time-courses, we analyzed correlations between the time-courses from the two experiments. As expected, only acetyl-CoA showed low correlation coefficient (Fig. S2). Even in a single experiment, this metabolites showed large SD compared to the other metabolites (Fig. S1a). Thus, the quantified concentration of this metabolite was not reliable because of its low stability. In contrast, the 3PG, 2PG, and PEP showed high correlations in significant level (P < 0.05). Time course of 2PG in Fig. 3 was not reliable because of the large SD especially at first 30 min; however the one in Fig. S1a showed smaller SD and similar pattern compared to the time course of 3PG. This indicates the high activity of reversible reaction by phosphoglycerate mutase (EC 5.4.2.1), which would contribute to the different time-course pattern of 3PG and 2PG, compared to upstream metabolites, such as F6P, F1,6P, and DHAP.

In this experiment, we analyzed lactate concentration in the medium to estimate the activity of lactate dehydrogenase (LDH, EC 1.1.1.27). The monotonic increasing of lactate in the medium (Fig. S1a) indicated the catalyzing pyruvate to lactate is dominant rather than the reversible reaction.

3.2.3 Energy metabolism

The adenylate and guanylate energy levels were almost constant up to 60 min and subsequently decreased gradually (Fig. 4a). The ATP level decreased slightly, whereas the AMP level increased and the ADP level remained nearly constant. Thus, the ratio of AMP/ATP was increased, suggesting an increase in ATP utilization (Fig. 4b). Similarly, the GTP level declined, whereas both the GDP and GTP levels remained nearly constant, resulting in an approximate twofold increase in the GMP/GTP ratio (Fig. 4c).
Fig. 4

Time courses of adenylate and guanylate energy charges (a), ATP, ADP and AMP (b), and GTP, GDP and GMP (c)

The increase in ATP utilization might further support the involvement of apoptosis because apoptosis is an energy-dependent process (Halestrap 2005). In contrast, eugenol, which induces non-apoptotic cell death (Coburn 2009), reduced the utilization of ATP (Koh et al. 2013). These data suggest that ATP utilization may be a useful marker for determining which cell death pathways are activated.

3.2.4 Changes in polyamine and oxidative stress-related metabolism

The time-courses for the concentrations of metabolites in the polyamine and glutathione synthesis pathways are described in Fig. 5. The time-courses for arginine and ornithine were slightly increased, whereas the time-courses for polyamines, including putrescine, spermidine and spermine, were slightly decreased (Fig. 5a). If the NaF treatment induced necrosis-like cell death, the activation of these polyamine pathways, which are necessary for membrane synthesis (Coburn 2009; Xie et al. 2007) possibly to compensate for the damage to membranes (Koh et al. 2013), is expected. However, the observed profile showed that this was not the case, suggesting the induction of non-necrotic cell death.
Fig. 5

Time courses of changes in the levels of oxidative stress-related metabolites. Polyamine, cysteine, glutathione and taurine synthesis pathways (a), ratio of methionine sulfoxide/methionine and GSSG/GSH (b), and cysteine-glutathione disulphide (c)

Cysteine was not detected up to 30 min, and subsequently its level dramatically increased. Both reduced glutathione (GSH) and oxidized glutathione (GSSG) remained almost constant up to 30 min. Subsequently, GSSG increased approximately twofold, while GSH dramatically decreased at 60 min and gradually recovered to its initial concentration. In fact, it is likely that oxidative stress increased in the late phase (after 30 min) based on the time-courses for the ratios of GSSG/GSH and methionine sulfoxide (oxidized metabolite of methionine)/methionine (Fig. 5b) and cysteine-glutathione disulphide, a molecule formed upon oxidative stress of gluthathione (38, 39) (Fig. 5c). Taken together with ATP utilization, these changes might be considered to be a result of cell injury induced by NaF. Downstream of cysteine in this pathway, glutamine and glutamic acid levels were not correlated with cysteine while glycine showed a similar pattern to GSH. Hypotaurine and taurine were also dissimilar to the cysteine time-course. Thus, only glycine positively correlated with these oxidative-stress profiles among the amino acids.

4 Discussion

The CE-TOF-MS metabolome analysis demonstrated that NaF increased fructose 1,6-phosphate and 2-phospho-glycerate (2PG; substrate of enolase), and maintained nearly constant levels of PEP (product of the enolase reaction) and pyruvate (endproduct of glycolysis) during the early stage of NaF-induced apoptosis in human oral squamous cell line (HSC-2). These results suggest that NaF may stimulate the onset of glycolysis, but inhibit the enolase reaction in oral HSC-2 cells, similar to that reported in bacterial systems (Guha-Chowdhury et al. 1997; Hata et al. 1990; Kaufmann and Bartholmes 1992; Takahashi and Washio 2011). NaF was also found to inhibit the TCA cycle progression, suggesting the presence of multiple initial target molecules of NaF.

The present study also demonstrated that NaF, which induces apoptosis, increased ATP utilization without affecting polyamine production. In contrast, eugenol, which induces necrotic cell death, reduced ATP utilization and elevated the putrecine level (Koh et al. 2013). These data suggest that ATP utilization may be an apoptosis marker, while polyamine production may be a necrotic marker. In contrast, both NaF (this study) and eugenol (Koh et al. 2013) increased the intracellular levels of oxidized metabolites such as GSSG, methionine sulfoxide and cysteine-glutathione disulphide, suggesting that these oxidative metabolites may be non-specific markers of cytotoxicity regardless of the type of cell death (apoptosis or necrosis). Addition of SOD and catalase significantly reduced the cytotoxicity of sodium ascorbate, but not the cytotoxicity of NaF, suggesting the involvement of intracellular ROS in the NaF-induced cell death (Acra et al. 2012). Further experiments with other apoptosis- and necrosis-inducing agents are needed to confirm these proposals.

The limitation of study is that we profiled only metabolite concentrations. Because most of the metabolites changed dynamically, flux analysis that requires steady-state condition is not suitable here; however the experiments with labelled metabolites, such as 13C-glucose and 13C-lactate, would help with better understanding of metabolic pathways. Also, several metabolites, such as acetyl-CoA, showed low consensus between independent experiments. It remains to be investigated whether NaF induces similar changes in normal oral cells.

We have recently reported that NaF induced the enhanced expression and dephosphorylation of the pro-apoptotic Bad protein and detachment of carbonic anhydrase II (CAII) from the Bad-CAII complex to facilitate apoptosis via formation of the Bad-Bcl-2 complex. Knockdown of Bad and CAII mRNAs by siRNA inhibited and enhanced NaF-induced caspase activation, respectively, suggesting that CAII may negatively regulate NaF-induced apoptosis by forming a complex with Bad (Otsuki et al. 2011). BAD has been reported to be associated with hexokinase (also known as glucokinase), and phosphorylated Bad forms large complexes with protein kinase A, protein phosphatase 1, and WAVE-1 in rat hematopoietic cells (Danial et al. 2003). The biological significance of these associations to NaF-induced cytotoxicity remains to be investigated.

5 Concluding remarks

In conclusion, the present study identified inhibition of the enolase reaction and TCA cycle progression as initial targets for the induction of NaF-induced apoptosis. As far as we know, there is no study that has investigated the changes in the intracellular concentrations of metabolites during cell death of human OSCC cell lines. It is highly probable that the inhibition of enolase reaction and TCA cycle progression at early stage is specific to NaF, whereas the increase of ATP utilization at later stage may be common to apoptotis-inducing agents, but not to necrosis-inducing agents. Systematic studies with numerous cytotoxic compounds are underway to confirm this point. Further investigation of the link between enolase inhibition and subsequent apoptosis marker expression may contribute to the safe clinical use of fluoride in dentistry.

Notes

Acknowledgments

The authors thank Prof. Akito Tomomura for his invaluable suggestions. This work was supported by research funds from the Yamagata Prefectural Government and the City of Tsuruoka, and in part by a Grant-in-Aid for Challenging Exploratory Research and Scientific Research (C) from the Ministry of Education, Culture, Sports, Science and Technology of Japan (H. Sakagami, No. 25670897, S. Tanaka, No. 24593164).

Supplementary material

11306_2013_576_MOESM1_ESM.ppt (252 kb)
Supplementary material 1 (PPT 252 kb)

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Hiroshi Sakagami
    • 1
  • Masahiro Sugimoto
    • 2
  • Shoji Tanaka
    • 3
  • Hiromi Onuma
    • 2
  • Sana Ota
    • 2
  • Miku Kaneko
    • 2
  • Tomoyoshi Soga
    • 2
  • Masaru Tomita
    • 2
  1. 1.Division of PharmacologyMeikai University School of DentistrySakadoJapan
  2. 2.Institute for Advanced BiosciencesKeio UniversityTsuruokaJapan
  3. 3.Division of Oral DiagnosisMeikai University School of DentistrySakadoJapan

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