Effects of Mainstream Cigarette Smoke on the Global Metabolome of

492

Chem. Res. Toxicol. 2009, 22, 492–503

Effects of Mainstream Cigarette Smoke on the Global Metabolome of Human Lung Epithelial Cells Suryanarayana V. Vulimiri,*,† Manoj Misra,† Jonathan T. Hamm,† Matthew Mitchell,‡ and Alvin Berger‡,§ A. W. Spears Research Center, Lorillard Tobacco Company, 420 North English Street, Greensboro, North Carolina 27420, and Metabolon, 800 Capitola DriVe, Suite 1, Durham, North Carolina 27713 ReceiVed August 28, 2008

Metabolomics is a technology for identifying and quantifying numerous biochemicals across metabolic pathways. Using this approach, we explored changes in biochemical profiles of human alveolar epithelial carcinoma (A549) cells following in vitro exposure to mainstream whole smoke (WS) aerosol as well as to wet total particulate matter (WTPM) or gas/vapor phase (GVP), the two constituent phases of WS from 2R4F Kentucky reference cigarettes. A549 cells were exposed to WTPM or GVP (expressed as WTPM mass equivalent GVP volumes) at 0, 5, 25, or 50 µg/mL or to WS from zero, two, four, and six cigarettes for 1 or 24 h. Cell pellets were analyzed for perturbations in biochemical profiles, with named biochemicals measured, analyzed, and reported in a heat map format, along with biochemical and physiological interpretations (mSelect, Metabolon Inc.). Both WTPM and GVP exposures likely decreased glycolysis (based on decreased glycolytic intermediaries) and increased oxidative stress and cell damage. Alterations in the Krebs cycle and the urea cycle were unique to WTPM exposure, while induction of hexosamines and alterations in lipid metabolism were unique to GVP exposure. WS altered glutathione (GSH) levels, enhanced polyamine and pantothenate levels, likely increased β-oxidation of fatty acids, and increased phospholipid degradation marked by an increase in phosphoethanolamine. GSH, glutamine, and pantothenate showed the most significant changes with cigarette smoke exposure in A549 cells based on principal component analysis. Many of the changed biochemicals were previously reported to be altered by cigarette exposure, but the global metabolomic approach offers the advantage of observing changes to hundreds of biochemicals in a single experiment and the possibility for new discoveries. The metabolomic approach may thus be used as a screening tool to evaluate conventional and novel tobacco products offering the potential to reduce risks of smoking. Introduction Metabolomics is a new approach that utilizes high-throughput identification, quantification, and characterization of biochemicals (4500 chemical compounds (6) including free radicals and oxidants (7) capable of inducing lung epithelial injury (8). To date, inhalation toxicology studies have been performed to study the exposure effects of complex mixtures such as cigarette smoke in rodent models (9, 10) and transcriptional changes in cell culture systems at the gene level using an “omic” approach (11), but metabolomic approaches have not been previously reported. Metabolomics is expected to provide useful information about changes in endogenous metabolic pathways of cultured lung cells, validating and expanding what has been learned using targeted analytical approaches and the aforementioned in vivo systems. In the present study, using a global metabolomic approach, applied for the first time in tobacco research, we investigated wet total particulate matter (WTPM) and gas/vapor phase (GVP), the two primary, physically separable component phases of mainstream cigarette smoke, or whole smoke (WS) from

10.1021/tx8003246 CCC: $40.75  2009 American Chemical Society Published on Web 01/22/2009

Cigarette Smoke on A549 Cell Metabolomics

Chem. Res. Toxicol., Vol. 22, No. 3, 2009 493

2R4F Kentucky reference cigarettes, as affecters of the metabolic pathways of A549 cells. The purpose of the present study was (1) to validate the methodology; (2) to determine if this global methodology may uncover previously unknown biochemical perturbations; (3) to determine if this approach may be useful for verifying/substantiating biochemical changes previously observed using targeted analytical approaches; and (4) to generate future testable hypotheses, likely using targeted, specific analytical approaches. The information acquired herein may facilitate identification of putative early biological indicators, which could serve as novel biomarkers in themselves, or provide a scientific basis of support for related biomarkers of exposure and effect. Eventually, results from metabolomic experiments will be used to develop disease-specific biomarker assays associated with cigarette smoke exposure.

Materials and Methods Cell Culture Supplies. Human type II alveolar epithelial carcinoma (A549) cells were purchased from American Type Culture Collection. Cell culture flasks (75 cm2) and 100 mm tissue culture dishes were from Corning (Corning, NY), and 0.25% Trypsin-EDTA solution, gentamicin, and nutrient mixture F-12 Ham (N8641) were purchased from Sigma (St. Louis, MO). Heat-inactivated fetal bovine serum (FBS), Hank’s balanced salt solution (HBSS), L-glutamine, and Dulbecco’s PBS (DPBS) were from GIBCO (Grand Island, NY). All reagents used for MS were Fisher Scientific Optima grade. Cell Culturing. A549 cells were routinely grown to 60-70% confluence in nutrient mixture F-12 Ham’s complete medium (CM) supplemented with 10% FBS, 2 mM L-glutamine, and 0.01 mg/mL gentamicin in a humidified 37 ( 2 °C incubator with 5% CO2. On average, the 75 cm2 flasks yielded ∼3 × 106 cells with ∼98% viability as determined with a NucleoCounter (New Brunswick Scientific, Edison, NJ). The serum-free medium (SFM) used for exposures was identical to CM but lacked FBS. GVP and WTPM Collection. 2R4F Kentucky reference cigarettes (University of Kentucky Research Foundation, Lexington, KY) were conditioned at 23 °C and 60% relative humidity for at least 18 h prior to smoking. The cigarettes were smoked on a Borgwaldt Technik RM-20/CS 20 port rotary smoking machine (Hamburg, Germany) under Federal Trade Commission (FTC) conditions (35 mL puff volume, 2 s draw, and 1 min interval) onto Cambridge filter pads. These glass fiber filter pads collected smoke particulate matter with greater than 99% efficiency under these smoking conditions. The GVP, comprising permanent gases, volatile compounds, and vapors, which passed through the pads, was collected into ice-cold DPBS and adjusted with the same buffer to a final concentration of 10 mg/mL, expressed as the equivalent mass of filtered WTPM accompanying the trapped GVP. The amount of WTPM collected on the filter pad was measured by taking the difference in the pad weight with and without WTPM and was then extracted with a known amount of dimethyl sulfoxide (DMSO). Depending on the weight of the WTPM, a volume of DMSO sufficient to make a final concentration of 40 mg/mL was added, and the WTPM was extracted into the DMSO. This extract was stored at -70 °C for further use (12). Note that WTPM contained total particulate matter (TPM), often referred to as “tar” plus nicotine and water. The GVP was utilized fresh (within 1 h of smoking) for cellular exposure, and WTPM was frozen at -20 °C.

Figure 1. Cytotoxicity EC50 determination of A549 cells exposed to WS by NRU assay. Cells were exposed to fresh WS from 2R4F cigarettes as described in the Materials and Methods, and the EC50 value for cytotoxicity was determined by the NRU assay.

Dosing A549 Cells with WTPM and GVP. Approximately 5.0 × 105 A549 cells were seeded into 75 cm2 flasks and incubated at 37 °C in presence of 5% CO2 in a humidified cell culture incubator for 72 h until they reached ∼70% confluence. The choice of concentrations for WTPM or GVP was based on in-house as well as historical data as an LC50 of ∼50 µg/mL (13). The GVP and WTPM were diluted further with DPBSSFM and 0.5% DMSO-SFM, respectively, to final concentrations of 5, 25, and 50 µg/mL. DPBS- and 0.5% DMSO-SFM were used as corresponding controls, respectively, for GVP or WTPM. A549 cells were washed once with SFM and exposed to different doses of GVP-DPBS-SFM and WTPM-DMSO-SFM with corresponding solvent controls for 1 or 24 h. Serum-free conditions were used to avoid volatiles interacting with serum proteins. For both exposures, the solvent concentration was maintained constant. Dosing A549 Cells with 2R4F WS. A custom-designed Plexiglas WS exposure chamber (40 cm L × 31.5 cm W × 14 cm H) was connected to a 20 port rotary smoking machine (Borgwaldt Technik) on the inlet side, and the outlet of the chamber was connected to a piston separated by a Cambridge filter pad. The smoking machine was equipped with a butt-length infrared sensor to prevent the cigarettes from being burned beyond a set length. When the fire cone came within the IR sensor field, the current puff was stopped prior to completion, resulting in a partial puff (ranging from 12.01 to 12.07 puffs or ∼12 puffs). The chamber was equipped with a small fan connected to a power supply (Lambda, model LQ-533) to uniformly mix WS in the exposure chamber. The cytotoxicity of WS was determined by neutral red uptake (NRU) assay (14) with modifications (15). The half-maximal effective concentration (EC50) of mainstream WS from 2R4F, which caused cytotoxicity in A549 cells, was determined as ∼six cigarettes (Figure 1). Approximately 1 × 106 A549 cells were seeded in Ham’s F-12 CM into 100 mm tissue culture dishes at 37 ( 2 °C in the presence of 5% CO2 in a humidified cell culture incubator for about 72 h until they reached ∼70% confluence. Cells were washed 1× with 10 mL of HBSS and changed to 2

494

Chem. Res. Toxicol., Vol. 22, No. 3, 2009

mL of Ham’s F-12 SFM for exposure to air or cigarette smoke. Cells were exposed to 12 puffs of either air puffed from unlit 2R4F cigarettes (controls) or WS puffed from two, four, or six 2R4F cigarettes, smoked on the rotary smoker. After exposing A549 cells to air or WS, an additional 10 mL of SFM was added to the dishes, the lids were closed, and the cells were transferred to a humidified cell culture incubator with 5% CO2 for 1 or 24 h. Preparation of Cell Pellets for Analysis. After completion of exposure, 1 mL of exposure medium from each replicate was stored at -80 °C. Cells were washed with 10 mL of HBSS, trypsinized with 2 mL of 0.25% Trypsin-EDTA, and washed 2× with ice-cold DPBS for determination of cell counts in a NucleoCounter. A cell suspension volume containing ∼1.5 × 106 cells from each replicate sample was pelleted, flash frozen in liquid nitrogen, and stored at -80 °C. Cell pellets were shipped to Metabolon, Inc., on dry ice for protein determination (Bradford kit, Sigma-Aldrich) and subsequent metabolomics. Sample Preparation for Metabolomics. Biochemicals were extracted from A549 cell pellets using an automated MicroLab STAR system (Hamilton Co., Salt Lake City, UT). Cell pellets were suspended in 200 µL of water. From this suspension, 100 µL was taken for extraction, 25 µL was used for Bradford protein analysis, and 25 µL was used to create a common pooled sample (CMTRX). The CMTRX was used to provide quality control results for the overall extraction and analysis process. The cell pellet aliquot was treated with 450 µL of methanol containing recovery standards (fluorophenylglycine, tridecanoic acid, and cholesterol-d6) and shaken for 2 min at 675 strokes/ min on a Geno Grinder 2000 (Glen Mills Inc., Clifton, NJ). The extract was centrifuged at 3000 rpm for 5 min at 4 °C. The supernatants were divided into aliquots for LC/MS and GC/ MS analyses. Aliquots were placed on a TurboVap (Zymark) to evaporate solvent under nitrogen and then dried under vacuum overnight in a centrivap concentrator (Labconco Inc., Kansas City, MO). Samples were maintained at 4 °C throughout the extraction process. Quality control standards were added prior to analysis to monitor injection, chromatographic, and instrument reproducibility. For LC/MS analyses, extract aliquots were reconstituted in 10% MeOH and 0.1% formic acid, containing standards (leucine-d3, chlorophenylalanine, bromophenylalanine, phenylalanine-d7, benzophenone-d10, tyrosine-d4, and amitryptyline) at fixed concentrations. GC/MS aliquots were derivatized with 50 µL of a solution containing equal parts of N,Obis[trimethylsilyl]trifluoroacetamide (BSTFA) and acetonitrile (ACN):dichloromethane (DCM):cyclohexane (5:4:1, v/v/v) with 5% triethanolamine (TEA), which contained standards (C4 to C18 alkylbenzenes), and were placed at 60 °C for 1 h. Samples were randomized prior to MS analyses. The sample identity was blinded to investigators until data curation completion. LC/MS. LC/MS was carried out using a Surveyor HPLC (ThermoElectron Corp., San Jose, CA) with an electrospray ionization (ESI) source coupled to a linear ion trap quadrupole (LTQ) mass spectrometer (ThermoElectron Corp.). Briefly, cell extracts were loaded onto a 100 mm × 2.1 mm, 3 µm particle, Aquasil column (ThermoElectron Corp.) via a CTC autosampler (LeapTechnologies, Carrboro, NC) and gradient eluted with 0% B for 4 min, 0-50% B for 2 min, 50-80% B for 5 min, and 80-100% B for 1 min; maintained at 100% B for 2 min. Solvent A was 0.1% formic acid in H2O; solvent B was 0.1% formic acid in MeOH. The mass spectrometer flow rate was 200 µL/ min. The LTQ acquired full scan mass spectra (99-1500 m/z) while switching polarity to monitor negative and positive ions. An LTQ-Fourier transform ion cyclotron resonance (FTICR)

Vulimiri et al.

hybrid MS (ThermoElectron Corp.) was operated at 50000 resolving power with a mass measurement error (10 ppm using gradient conditions as above to confirm reported biochemicals present above the instrument’s limit of detection (LOD). GC/MS. Samples were analyzed on a Thermo-Finnigan Trace dual-stage quadrupole (DSQ) fast-scanning single-quadrupole MS, operated at unit mass resolving power. The GC column was 5% phenyl, 95% dimethyl polysiloxane, 20 m × 0.18 mm; 0.18 µm phase thickness. The column was programmed from 60 to 340 °C in an 18 min run time. The instruments were operated using electron impact ionization with 50-750 amu scan range, tuned, and calibrated daily for mass resolution and mass accuracy. Biochemical Identification. We subjected the complete data set for all cellular exposure analyses and utilized the largest two component coordinates, the components showing the optimum variance, and identified the most significantly altered biochemicals. Biochemicals were identified by automated comparison to library entries in Metabolon’s metabolite library. The combination of mass spectral and chromatographic properties was used to assign an identity to specific biochemicals. The identification of named chemical entities was based on comparison to internal metabolomic library entries of purified standards run on the same analytical platform. Peptides were identified using standard tandem MS sequencing techniques (16). Data Analysis and Statistical Analysis. Numbers were derived from raw detector counts of the mass spectrometers. Following data extraction, automated quality control checks, and curation (confirming that biochemicals were correctly named by the automated software), data were presented as a series of peak area quantities. Raw area counts for a biochemical were divided by the median value for that biochemical across all treatments and days, setting the medians equal for each day, to reduce interday tuning differences. Data were then corrected for Bradford protein content. Statistical analysis of data was performed using JMP (SAS, http://www.jmp.com) and “R” (http://cran.r-project.org/), a freely available, open-source software package. ANOVA was performed on the full factorial design. A log transformation was applied to the observed relative concentrations for each biochemical because, in general, the variance increased as a function of a biochemical’s average response and because ratios were being compared. Those biochemicals having detectable levels in a majority of the samples were included in the analyses. Specifically, for the GVP and WTPM data sets, at least a 50% fill rate (above the LOD in at least half of the samples) in one of the two groups was required, and this resulted in the exclusion of some biochemicals. For the WS cells, no biochemicals were excluded utilizing the above rule. Missing values were assumed to be below the LOD and were imputed with the minimum for that biochemical across all groups. Welch’ two-sample t tests were used to compare each dose to the 0 dose, at each time point evaluated, for all experiments. The median relative standard deviation (RSD) per group from experiments evaluating individual WTPM and GVP samples (Table S1 of the Supporting Information) ranged from 20 to 30%. For analysis of pooled cell pellets derived from experiment 1 (Table S2 of the Supporting Information), an RSD value of 30% was used to calculate p values [i.e., sample standard deviations (SDs) in the denominator for the t test for each group were based on an RSD of 30%], with significance evaluated at p < 0.05, on nonlog transformed values. The 30% value was based on the individual data and applied to the pooled data; only biochemicals not detected in the individual data were considered.



Table 1. Analysis of Cambridge Filter Pad after Passing 2R4F WS in the Exposure Chambera no. of cigarettes smoked 0 2 4 6

to 24 h, by both WTPM (except low dose), GVP, and WS (Table 2). These biochemicals were mapped on to Z score plots, which represent the numbers of SD units the study samples are above or below the mean of the control group for a given biochemical and calculated by the formula: z ) [x - mean (x control)]/[SD(x control)], wherein x is the value of the biochemical from a replicate (represented in Figure S1 of the Supporting Information). Data are expressed as “mScores”, which are the means of absolute values of individual Z scores, and indicate how drastically sample data points are dispersed from the mean. WTPM after 24 h and GVP after 1 h showed higher mScores, indicating late and early impact, respectively, on the biochemicals in A549 cells (Table 2). For the WS exposure, the mScores showed a dose-response with the number of cigarettes for both 1 and 24 h exposures. Notably, more biochemicals were up-regulated at both time points, while downregulation was prominent 1 h after WS exposure (Table 2). Effect of WTPM, GVP, and WS Exposure on the Biochemicals of A549 Cells. Several biochemicals were affected by the different cigarette smoke phases, in dose- and timedependent manners. Data are expressed as fold-changes (red, up; green, down; and uncolored, no change; p < 0.05), relative to corresponding time-matched control groups (Tables S1-S3 of the Supporting Information). Figure 2 shows the significant changes seen in the numbers of biochemicals whether upregulated or down-regulated following 1 or 24 h of exposure to WTPM, GVP, or WS for the major biochemical pathways, that is, amino acid (panel A), carbohydrate (panel B), lipid (panel C), energy (panel D), nucleotide (panel E) and coenzymes, vitamins, and other minor ones (panel F). As can be seen, WS had a higher impact on several of the pathways as compared to WTPM or GVP, except that GVP showed a higher impact on lipid metabolism 24 h after exposure. Amino Acid Metabolism. Levels of several amino acids were decreased after 1 h of WTPM exposure followed by an increase after 24 h of exposure. In contrast, GVP caused an increase in more amino acids after 1 h than after 24 h of exposure. Exposure of A549 cells to 2R4F cigarette WS caused both up- and downregulation of amino acids at 1 h but more up-regulation after 24 h of exposure (Figure 2A).

mean ( SD no. of puffs 12.03 ( 0.02 12.01 ( 0.01 12.07 ( 0.07 12.06 ( 0.05

WTPM (mg) 0.0 ( 0.0 5.10 ( 1.08 10.65 ( 3.32 17.63 ( 1.52

water (mg) 0.86 ( 0.14 0.48 ( 0.24 2.54 ( 1.45 6.35 ( 0.81

nicotine (mg) 0.00 ( 0.00 0.17 ( 0.01 0.37 ( 0.08 0.63 ( 0.04

a

Cigarettes were smoked under FTC conditions. Data represent the amounts present (in mg) in the designated number of cigarettes in ∼12 puffs. WTPM represents total particulate matter (TPM) with water and nicotine.

Cigarette smoke-induced biochemical alterations were also analyzed by principal component analysis (PCA) using computer software (http://faculty.fuqua.duke.edu/∼kamakura/Downloads/ Principal Components.zip). This involved the eigenvalue decomposition of a data covariance matrix, after mean centering the data for each attribute, and the results were generated as component scores and factor loadings. The data were subjected to orthogonal linear transformation to a new coordinate system such that the greatest variance lies on the first coordinate (named the first principal component), the second greatest variance lies on the second coordinate, etc. We subjected the complete data set for all cellular exposure analyses and utilized the largest two component coordinates, the components showing the optimum variance, and identified the most significantly altered biochemicals.

Results Cytotoxicity by NRU Assay. The cytotoxicity of WS was evaluated in A549 cells by the NRU assay. The EC50 of WS from 2R4F cigarettes causing 50% cytotoxicity in A549 was six cigarettes.(Figure 1). Analysis of particulate collected on Cambridge filter pads in our system demonstrated that WS displayed increases in WTPM, water, and nicotine content with increasing numbers of cigarettes smoked (Table 1). Effect of 2R4F Cigarette Smoke WTPM, GVP, and WS on Biochemical Pathways of A549 Cells. Most changes in biochemicals were observed after 1 h of exposure as compared

Table 2. Dose and Time Dependence of Biochemicals Significantly Changed in A549 Cells after Exposure to 2R4F Cigarette WTPM and GVPa WTPM 1 h WTPM exposure

24 h WTPM exposure

WTPM (µg/mL)

up-regulated

down-regulated

total changed

mScore

WTPM (µg/mL)

up-regulated

down-regulated

total changed

mScore

5 25 50

1 5 5

8 21 31

9 26 36

0.91 1.44 1.11

5 25 50

26 9 9

1 6 16

27 15 25

1.54 1.41 1.49

GVP 1 h GVP exposure

24 h GVP exposure

GVP (µg/mL)

up-regulated

down-regulated

total changed

mScore

GVP (µg/mL)

up-regulated

down-regulated

total changed

mScore

5 25 50

14 14 10

8 4 10

22 18 20

2.00 1.87 1.25

5 25 50

10 5 6

0 7 4

10 12 10

1.54 1.41 1.49

WS 1 h WS exposure

24 h WS exposure

no. of cigarettes

up-regulated

down-regulated

total changed

mScore

no. of cigarettes

up-regulated

down-regulated

total changed

mScore

2 4 6

36 32 41

15 37 33

51 69 74

1.87 2.47 2.74

2 4 6

47 46 45

14 11 8

61 57 53

2.62 3.37 4.36

a WTPM was extracted with DMSO, and GVP was collected in DPBS as described in the Materials and Methods. A549 cells were exposed to air (control) or WS from 2, 4, and 6 2R4F cigarettes as described in the Materials and Methods. mScore is the mean of absolute values of the summarized individual Z scores. Higher mScores represent larger changes in the biochemicals for the particular group in question.

496


Vulimiri et al.

Figure 2. Effects of cigarette smoke phases and WS on the metabolic pathways of A549 cells. A549 cells were exposed to 5 (dose #1), 25 (dose #2), and 50 (dose #3) µg/mL WTPM or GVP; or WS from 2 (dose #1), 4 (dose #2), and 6 (dose #3) cigarettes for 1 or 24 h as described in the Materials and Methods. Biochemicals significantly altered over the corresponding controls were identified and plotted as up-regulated (above the X-axis) or down-regulated (below the X-axis).

GSH/Peptide Metabolism. Exposure of A549 cells to WTPM (24 h) and GVP (1 h) depleted GSH levels statistically significantly (p < 0.05), while GSSG levels were unaffected, causing a decrease in the GSH/GSSG ratio, suggestive of oxidative stress (Figure 3). In contrast, exposure to WS in A549 cells caused a 36-45-fold increase in GSH after 1 h of exposure, whereas GSSG showed a modest increase after 1 h (Table S1 of the Supporting Information). Two dipeptides, γ-glutamylcysteine (γ-GluCys) and γ-glutamylglutamine (γ-GluGln), were increased 1 h after WTPM exposure (Figure 3), while only γ-GluCys was increased after 1 h of GVP exposure, suggesting altered kinetics of GSH synthesis. Levels of γ-GluCys and γ-GluGln showed a dose-dependent increase with an increasing dose of WS 1 and 24 h after exposure. Levels of Gln, which also feed into the glutathione cycle, were significantly increased

1 h after WTPM exposure but depleted with GVP exposure at selected doses. WS caused a marked increase in Gln levels predominantly after 24 h of exposure (Figure 3). Urea Cycle and Polyamine Metabolism. As levels of amino acids changed, effects on urea cycle activity, especially 24 h after WTPM exposure, were observed (Figure 4). In particular, ornithine showed a significant increase at all doses with WTPM after 24 h of exposure. However, only a low dose of GVP caused a significant increase in ornithine 1 h after exposure. Following WS exposure, arginine, ornithine, and citrulline increased after 1 and 24 h, consistent with increased amino acid entry into the urea cycle (Figure 4). As for polyamine metabolism, GVP, but not WTPM, caused an increase in the polyamine putrescine after 1 h of exposure and a modest increase after 24 h of exposure.



Figure 3. Cigarette smoke phases and WS on glutathione metabolism. A549 cells were exposed to WTPM or GVP or WS as described in Figure 2. Gray-filled bars, dose #1; black-filled bars, dose #2; and clear bars with no filling, dose #3. Cysteine was not detected with WTPM- or GVPexposed A549 cells. Glutamate is a precursor to Gln. For simplicity, single and multiple step reactions alike are shown by a single line arrow. Data from representative biochemicals with significant changes are shown. *p < 0.05, as compared to the corresponding control. Not all biochemical steps are shown in Figures 3-6. For simplicity, single and multiple step reactions alike are shown by a single line arrow. Biochemicals upregulated, down-regulated, and with no change are shown in gray, black, and clear boxes, respectively.

Putrescine levels showed a dose-dependent increase (3.4-7.0) after 24 h with all WS doses similar to GVP (Figure 4). Carbohydrate Metabolism. Exposure to WTPM decreased fructose, fructose 1-phosphate (F1P), 3-phosphoglycerate (3PG), and phosphoenolpyruvate (PEP) in A549 cells (Figure 5) and increased lactate after 24 h of exposure (data not shown). Glucose and the amino sugar, UDP-N-acetylglucosamine, increased significantly 1 h after GVP exposure (data not shown). A general decrease in the levels of biochemicals from glycolysis, sorbitol, and pentose phosphate pathways was observed after 1 h with WS exposure with sorbitol and fructose levels showing pronounced reductions ranging from 50 to 60% (Figure 5). However, after 24 h, sorbitol (2.5-10.4-fold) and

fructose (3.8-6.4-fold) were dramatically increased at all doses of WS exposure (Figure 5). Lipid Metabolism. Exposure of A549 cells to cigarette smoke phases also caused changes in lipid metabolism as evidenced by a dramatic increase in acetylcarnitine with all doses of WTPM and a small, but significant, increase with the high dose of GVP after 24 h of exposure (Figure 6A) and increased carnitine (data not shown) with GVP 24 h after exposure, suggesting changes in fatty acid β-oxidation. WS exposure also caused a dose-dependent increase in acetylcarnitine, which was more pronounced at 24 h (Figure 6A). Notably, WTPM (24 h) and GVP (1 h) induced high levels of phosphoethanolamine, a normal component of phosphatidylethanolamine (PE) degrada-

498


Vulimiri et al.

Figure 4. Cigarette smoke phases and WS on urea cycle and polyamine metabolism. A549 cells were exposed to WTPM or GVP or WS as described in Figures 2 and 3. Gray-filled bars, dose #1; black-filled bars, dose #2; and clear bars with no filling, dose #3. Citrulline and agmatine were not detected in WS-exposed A549 cells; arginosuccinate was not detected in WTPM-, GVP-, or WS-exposed cells. *p < 0.05, as compared to the corresponding control.

tion and synthesis (Figure 6B). WS exposure increased phosphoethanolamine ∼16.4-fold at 24 h with the high dose similar to the trends seen with GVP after 1 h and WTPM after 24 h of exposure (Figure 6B), suggesting that longer durations and higher doses increase phospholipid degradation and possibly membrane damage and apoptosis. Surprisingly, we did not detect many fatty acids in the cell pellet extracts initially from either WTPM or GVP exposure. Hence, we pooled the remaining aliquots of cell pellets from all of the replicates within the same treatment group to increase the amount of cellular material and reanalyzed with the same metabolomic approach. Several fatty acids were detected in pooled pellets, which were not detected earlier in single pellets, suggesting that increased cell numbers were needed to detect fatty acids in A549 cells (Table S2 of the Supporting Information). WTPM showed a modest, but significant, increase in arachidonic acid, a precursor of typically pro-inflammatory eicosanoids, while GVP induced a dose-dependent increase at all doses 1 h after exposure, suggesting an inflammatory response (Figure 6 C). WS also increased arachidonic acid levels by 1.3-1.7-fold after 24 h (Figure 6C).

Energy Metabolism. Among biochemicals in the Krebs cycle, citrate increased with GVP exposure, while WS exposure increased several citric acid cycle intermediates at both time points with greater impact after 24 h, including citrate, R-ketoglutarate, fumarate, and malate (Figure 7). This suggests increased processing of these biochemicals through the citric acid cycle to meet energy needs. Nucleotide Metabolism. Several nucleotides, such as AMP, NAD+, and GMP, showed a significant decrease with WTPM and GVP exposure. However, levels of ADP-ribose (ADPR), a byproduct of NAD, increased after 24 h of exposure with WTPM and after 1 h of exposure with GVP. With WS exposure, inosine (Ino)-related purines (xanthine, hypoxanthine, Ino, and inosine 1-phosphate) decreased while adenine (Ade)-containing purines [Ade, adenosine (Ado), AMP, and ADP] increased after 1 h. Among pyrimidines, TMP and uridine (Urd) showed strong decreases (40-60%) after 1 h (data not shown). Cofactor and Vitamin Metabolism. Pantothenate, a precursor for acetyl coenzyme A (AcCoA) and critical in fat synthesis (as a component of acyl carrier protein) and fatty acid synthetase, showed a dose-dependent increase after WTPM but not GVP



Figure 5. Cigarette smoke phases and WS on sorbitol, glycolysis, and coenzyme pathways. A549 cells were exposed to WTPM or GVP or WS as described in Figures 2 and 3. Gray-filled bars, dose #1; black-filled bars, dose #2; and clear bars with no filling, dose #3. Glucose-6-phosphate, fructose-6-phosphate, pyruvate, and acetyl Coenzyme A were not detected with WTPM-, GVP-, or WS-exposed cells. *p < 0.05, as compared to the corresponding control.

exposure (Figure 5). Following WS exposure, pantothenate and NAD+ increased at most doses at both time points, while NADP+ (all doses) and FAD+ (intermediate dose at both time points) also increased after 1 h (data not shown).

Discussion

as the highest dose of exposure, to minimize toxicity. Several biochemical classes were altered by exposure in our study with WS or its constituent physical phases in A549 cells, namely, amino acids and derivatives (glutathione, urea, and polyamine), carbohydrates, fatty acids and lipids, energy-related biochemicals, and nucleotides.

To our knowledge, this is the first time metabolomics has been used to study effects of mainstream whole cigarette smoke or its fractions on biochemical pathways in cell lines (or to study the effects of cigarette smoke in any capacity). The A549 cell line has been widely used in toxicology studies because of the metabolic and macromolecule processing roles being similar to normal human alveolar type II epithelial cells in xenobiotic interactions at the pulmonary epithelium (17). The half-maximal cytotoxic concentration (IC50) of cigarette smoke condensate (CSC) is ∼50 µg/mL in A549 cells (13), which was used herein

Glutathione is an efficient antioxidant providing protection against oxidative stress (18). Exposure to cigarette smoke or its condensate causes rapid depletion of GSH with efflux of GSSG in epithelial cells in vitro and in vivo (18-20). Consistent with these reports, we observed GSH depletion in A549 cells, with both smoke phases altering the GSH/GSSG ratios, suggestive of oxidative stress. Epithelial cells exposed to WTPM show decreased activities of glutathione peroxidase, γ-glutamylcysteine synthetase (γ-GCS), and glucose-6-phosphate dehydrogenase without changes in glutathione S-transferase and

500


Vulimiri et al.

Figure 6. Cigarette smoke phases and WS on lipid metabolism. A549 cells were exposed to WTPM or GVP or WS as described in Figures 2 and 3. Gray-filled bars, dose #1; black-filled bars, dose #2; and clear bars with no filling, dose #3. Biochemicals significantly altered by WTPM or GVP for acetylcarnitine (A), phosphoethanolamine (B), and arachidonic acid (C) are shown. *p < 0.05, as compared to the corresponding control.

Figure 7. Cigarette smoke phases and WS on Krebs cycle. Oxaloacetate, isocitrate, succinyl coenzyme A, and succinate were not detected in WTPM-, GVP-, or WS-exposed A549 cells. R-Ketoglutarate was not detected with WTPM or GVP exposure. Biochemicals up-regulated, downregulated, and with no change are shown in gray, black, and clear boxes, respectively.



Figure 8. PCA. The results of PCA were applied to the whole set of biochemical data, all measured variables with different subpathways. Score plot (PC1 vs PC2) of variables revealing putative biomarkers from different metabolic pathways in A549 cells following exposure to 2R4F cigarette smoke phases or WS. γ-GluGlu, γ-glutamylglutamate; IMP, inosine 5′-monophosphate.

glutathione reductase activities (18, 20). However, we observed increased levels (build up) of the γ-GluCys precursor with 1 h of exposure. Thus, decreased GSH levels are possibly due to decreased synthesis. GSH depletion often follows an increase in its levels as an adaptive response to oxidative stress due to up-regulation of γ-GCS in lung cells (21). Also, oxidative and peroxidative stress can increase GSH synthesis and turnover in lung (22) and other cell types (23). Consistent with these findings, we observed a striking elevation in GSH and γ-GC after WS exposure. Thus, changes in GSH and GSSG indicate that oxidative stress response was involved, but the directionality of the change needs to be verified in future studies with more specific methods than the global metabolomic method employed herein. Thus, quantitative assessment of GSH/GSSG ratio may be better obtained using a targeted method. During oxidative stress induced by cigarette smoke extract, the uptake and utilization of sulfur-containing amino acids, such as Cys and Met are elevated, leading to increased SAM and SAM/SAH ratios in A549 cells (24). However, we did not find any significant changes in SAM or SAM/SAH ratios in the present study, possibly because our highest concentration of WTPM used was only 50 µg/mL. One mechanism by which cigarette smoke stimulates cell proliferation in the airways of asthmatic smokers is by inducing the conversion of ornithine to polyamines via ornithine decarboxylase (ODC) activity (25), the committed step in polyamine production. Ornithine was increased by WTPM, GVP, and WS at differing doses and times, and the polyamine putrescine was altered with GVP and WS but not WTPM. Polyamines are signaling molecules involved in cell proliferation and differentiation (26), and increased cell proliferation has been observed in NCI-H292 human lung mucoepidemoid carcinoma cells exposed to low concentrations of cigarette smoke condensate (27). In the present experiment, the increase in putrescine under some conditions could be associated with mitogenicity (28). Elevated putrescine levels in A549 cells with GVP as well as WS in our study are consistent with a role for WS in tumor promotion. Although, the evidence that polyamines were affected by cigarette exposure was not striking as there were not changes to other polyamines and 5-methylthioadenosine (a marker of polyamine metabolism). One explanation could be that these related biochemicals were below limits of detection.

Aqueous extracts of cigarette smoke have been found to inhibit glycolytic activity but not to change membrane biophysical properties in human polymorphonuclear leukocytes (29), while GVP disturbs glycolysis and inhibits glyceraldehyde 3-phosphate dehydrogenase in pulmonary macrophages (30). Consistent with this, we observed decreased glycolysis biochemicals such as 3-PG and PEP in A549 cells with isolated smoke phases or WS. Upon WS exposure, levels of fructose and sorbitol changed in a consistent manner, indicating that the fructose is likely derived from sorbitol in the sorbitol dehydrogenase reaction. Sorbitol increases in response to stress and may contribute to apoptosis via increases in osmotic pressure in the cell (since sorbitol is not easily excreted from cells and builds up). In the sorbitol pathway, glucose + NADPH are converted to sorbitol and NADP+ via the aldose reductase step. Thus, high levels of sorbitol are associated with reduced NADPH, leading to a build up of GSSG due to reduced glutathione reductase activity. Thus, elevated sorbitol may contribute to apoptosis and oxidative stress recently and in experiments in human K562 myelogenous leukemia cells (31). Exposure to cigarette smoke phases or WS may have caused a significant increase in fatty acid β-oxidation, as evidenced by an increase in the pathway marker metabolites carnitine and acetylcarnitine in A549 cells. High levels of β-oxidation lead to an accumulation of acetyl CoA, which then combines with carnitine, forming acetylcarnitine. Heavy smokers exhibit higher lipolysis, leading to elevated serum free fatty acids in association with smoking (32), and this, in turn, likely leads to increased β-oxidation in cells following cellular uptake. Thiol depletion (33) and exposure to volatile and nonvolatile components of cigarette smoke cause lung injury (34) manifested by cells’ proceeding through apoptotic pathways at lower concentrations and necrosis at higher concentrations (35), as a result of mitochondrial damage (36). Consistent with these reports, we observed a 1.7-16.4-fold increase in phosphoethanolamine, a marker of phospholipid degradation, suggesting cell damage and possibly apoptosis with WTPM (as a late event), GVP (as an early event), and WS (both time points but more pronounced at 24 h), confirming the role and elucidating the mechanism of cigarette smoke in inducing cytotoxicity and possible membrane damage. Oxidative stress induces inflammatory responses in A549 cells (37), which was consistent with

502


increased release of unesterified arachidonate with WS exposure in our study. Lowered levels of Krebs cycle biochemicals with isolated smoke phase exposures were consistent with decreased glycolysis-related biochemicals and reduced availability of amino acids for transamination entry into the Krebs cycle. However, WS caused an increase in apparent Krebs cycle activity, which may be due to a complex interaction of cigarette smoke components in the WS. Pantothenate is a precursor of acetyl CoA in mammalian cells (38). The dramatic increase in pantothenate in A549 cells treated with WTPM and WS indicates that pathways utilizing acetyl CoA may have been altered. Genotoxic stimuli produced by cigarette smoke extracts activates poly(ADPR) polymerase (PARP), which breaks down NAD+ to nicotinamide and ADPR and marks for induction of inflammation, apoptosis, and oxidative stress in A549 cells (39). Consistent with these reports, we observed depleted NAD+ and increased ADPR by WTPM and GVP, suggesting that the smoke phases may have activated the PARP signaling cascade, leading to increases in inflammation, apoptosis, and oxidative stress. Overall, the major changes observed in A549 cell biochemical pathways following cigarette smoke exposure were those affecting amino acid metabolism (Gln), glutathione metabolism (GSH, γ-GluCys, and γ-GluGln), urea cycle (Arg), polyamines (putrescine), sorbitol pathway (sorbitol and fructose), Krebs cycle (citrate and R-ketoglutarate), lipid metabolism (phosphoethanolamine and acetylcarnitine), nucleotide metabolism (IMP), and cofactors (pantothenate) of which pantothenate, Gln, and GSH showed the most significant changes by PCA analysis (Figure 8). In summary, altered GSH/GSSG kinetics in A549 cells in the present study are consistent with the established knowledge that cigarette smoke induces oxidative stress in mammalian cells. Observations that increase in the polyamine putrescine levels are suggestive of cell proliferation and possible involvement of cigarette smoke in tumor promotion. Increased phospholipid degradation marked by an increase in phosphoethanolamine is suggestive of cytotoxicity. Increased arachidonic acid levels with GVP and WS exposure are suggestive of inflammatory response. However, further studies are warranted as subsequent follow up work, wherein key biochemicals should be measured using targeted approaches with stable isotope standards. Herein, using metabolomics, we identified changes in biochemicals that may be used as biomarkers for diseases related to chronic tobacco smoke exposure. Using human lung carcinoma cells, we broadly explored fundamental tobacco smokeassociated alterations in cellular biochemistry to provide a scientific basis for development of more informative indices of early disease-specific etiologic events. A logical extension of the current study would be to link pathway alterations in normal and cancerous lung epithelial cells to changes seen in other highthroughput platforms or to markers of disease in human clinical situations. The metabolomic approach may also serve as an improved screening tool to advance understanding of the biological consequences associated with conventional cigarette smoking products and have utility for evaluating novel, reduced risk products. Supporting Information Available: Biochemical pathway heat map of 2R4F cigarette WTPM and GVP-exposed A549 cells (Table S1), fatty acid heat map of 2R4F WTPM and GVPexposed A549 cells (Table S2), and biochemical heat map of 2R4F cigarette WS-exposed A549 cells (Table S3). Representa-

Vulimiri et al.

tive Z score plot (Figure S1). This material is available free of charge via the Internet at http://pubs.acs.org.

References (1) Clarke, C. J., and Haselden, J. N. (2008) Metabolic profiling as a tool for understanding mechanisms of toxicity. Toxicol. Pathol. 36, 140– 147. (2) Lawton, K. A., Berger, A., Mitchell, M., Milgram, K. E., Evans, A. M., Guo, L., Hanson, R. W., Kalhan, S. C., Ryals, J. A., and Milburn, M. V. (2008) Analysis of the adult human plasma metabolome. Pharmacogenomics 9, 383–397. (3) van Ravenzwaay, B., Cunha, G. C., Leibold, E., Looser, R., Mellert, W., Prokoudine, A., Walk, T., and Wiemer, J. (2007) The use of metabolomics for the discovery of new biomarkers of effect. Toxicol. Lett. 172, 21–28. (4) Khoo, S. H., and Al-Rubeai, M. (2007) Metabolomics as a complementary tool in cell culture. Biotechnol. Appl. Biochem. 47, 71–84. (5) Miller, M. G. (2007) Environmental metabolomics: A SWOT analysis (strengths, weaknesses, opportunities, and threats). J. Proteome Res. 6, 540–545. (6) Hecht, S. S. (2006) Cigarette smoking: Cancer risks, carcinogens, and mechanisms. Langenbecks Arch. Surg. 391, 603–613. (7) Church, D. F., and Pryor, W. A. (1985) Free-radical chemistry of cigarette smoke and its toxicological implications. EnViron. Health Perspect. 64, 111–126. (8) Lannan, S., Donaldson, K., Brown, D., and MacNee, W. (1994) Effect of cigarette smoke and its condensates on alveolar epithelial cell injury in vitro. Am. J. Physiol. 266, L92–L100. (9) Meng, Q. R., Gideon, K. M., Harbo, S. J., Renne, R. A., Lee, M. K., Brys, A. M., and Jones, R. (2006) Gene expression profiling in lung tissues from mice exposed to cigarette smoke, lipopolysaccharide, or smoke plus lipopolysaccharide by inhalation. Inhalation Toxicol. 18, 555–568. (10) Gebel, S., Gerstmayer, B., Bosio, A., Haussmann, H. J., Van Miert, E., and Muller, T. (2004) Gene expression profiling in respiratory tissues from rats exposed to mainstream cigarette smoke. Carcinogenesis 25, 169–178. (11) Sen, B., Mahadevan, B., and DeMarini, D. M. (2007) Transcriptional responses to complex mixtures: A review. Mutat. Res. 636, 144–177. (12) Pillsbury, H. C., Bright, C. C., O’Connor, K. J., and Irish, F. W. (1969) Tar and nicotine in cigarette smoke. J. Assoc. Off. Anal. Chem. 52, 458–462. (13) Miyashita, M., Willey, J. C., Sasajima, K., Lechner, J. F., LaVoie, E. J., Hoffmann, D., Smith, M., Trump, B. F., and Harris, C. C. (1990) Differential effects of cigarette smoke condensate and its fractions on cultured normal and malignant human bronchial epithelial cells. Exp. Pathol. 38, 19–29. (14) Borenfreund, E., and Puerner, J. A. (1985) Toxicity determined in vitro by morphological alterations and neutral red absorption. Toxicol. Lett. 24, 119–124. (15) Bombick, D. W., and Doolittle, D. J. (1995) The role of chemical structure and cell type in the cytotoxicity of low molecular weight aldehydes and pyridines. In Vitro Toxicol. 8, 349–356. (16) Kinter, M., and Sherman, N. (2000) Protein Sequencing and Identification Using Tandem Mass Spectrometry, Vol. 00, John Wiley & Sons, New York. (17) Foster, K. A., Oster, C. G., Mayer, M. M., Avery, M. L., and Audus, K. L. (1998) Characterization of the A549 cell line as a type II pulmonary epithelial cell model for drug metabolism. Exp. Cell Res. 243, 359–366. (18) Rahman, I., and MacNee, W. (1999) Lung glutathione and oxidative stress: Implications in cigarette smoke-induced airway disease. Am. J. Physiol. 277, L1067–L1088. (19) Li, X. Y., Donaldson, K., Rahman, I., and MacNee, W. (1994) An investigation of the role of glutathione in increased epithelial permeability induced by cigarette smoke in vivo and in vitro. Am. J. Respir. Crit. Care Med. 149, 1518–1525. (20) Rahman, I., Li, X. Y., Donaldson, K., Harrison, D. J., and MacNee, W. (1995) Glutathione homeostasis in alveolar epithelial cells in vitro and lung in vivo under oxidative stress. Am. J. Physiol. 269, L285– L292. (21) Rahman, I., Smith, C. A., Lawson, M. F., Harrison, D. J., and MacNee, W. (1996) Induction of gamma-glutamylcysteine synthetase by cigarette smoke is associated with AP-1 in human alveolar epithelial cells. FEBS Lett. 396, 21–25. (22) Deneke, S. M., and Fanburg, B. L. (1989) Regulation of cellular glutathione. Am. J. Physiol. 257, L163–L173. (23) Bea, F., Hudson, F. N., Chait, A., Kavanagh, T. J., and Rosenfeld, M. E. (2003) Induction of glutathione synthesis in macrophages by oxidized low-density lipoproteins is mediated by consensus antioxidant response elements. Circ. Res. 92, 386–393.

Cigarette Smoke on A549 Cell Metabolomics (24) Panayiotidis, M. I., Stabler, S. P., Allen, R. H., Ahmad, A., and White, C. W. (2004) Cigarette smoke extract increases S-adenosylmethionine and cystathionine in human lung epithelial-like (A549) cells. Chem.Biol. Interact. 147, 87–97. (25) Bergeron, C., Boulet, L. P., Page, N., Laviolette, M., Zimmermann, N., Rothenberg, M. E., and Hamid, Q. (2007) Influence of cigarette smoke on the arginine pathway in asthmatic airways: Increased expression of arginase I. J. Allergy Clin. Immunol. 119, 391–397. (26) Heby, O. (1981) Role of polyamines in the control of cell proliferation and differentiation. Differentiation 19, 1–20. (27) Luppi, F., Aarbiou, J., van Wetering, S., Rahman, I., de Boer, W. I., Rabe, K. F., and Hiemstra, P. S. (2005) Effects of cigarette smoke condensate on proliferation and wound closure of bronchial epithelial cells in vitro: Role of glutathione. Respir. Res. 6, 140. (28) Pegg, A. E. (1988) Polyamine metabolism and its importance in neoplastic growth and a target for chemotherapy. Cancer Res. 48, 759– 774. (29) Zappacosta, B., Persichilli, S., Minucci, A., Stasio, E. D., Carlino, P., Pagliari, G., Giardina, B., and Sole, P. D. (2001) Effect of aqueous cigarette smoke extract on the chemiluminescence kinetics of polymorphonuclear leukocytes and on their glycolytic and phagocytic activity. Luminescence 16, 315–319. (30) Green, G. M. (1985) Mechanisms of tobacco smoke toxicity on pulmonary macrophage cells. Eur. J. Respir. Dis. Suppl. 139, 82–85. (31) Marfe, G., Morgante, E., Di Stefano, C., Di Renzo, L., De Martino, L., Iovane, G., Russo, M. A., and Sinibaldi-Salimei, P. (2008) Sorbitolinduced apoptosis of human leukemia is mediated by caspase activation and cytochrome c release. Arch. Toxicol. 82, 371–377.

Chem. Res. Toxicol., Vol. 22, No. 3, 2009 503 (32) Hellerstein, M. K., Benowitz, N. L., Neese, R. A., Schwartz, J. M., Hoh, R., Jacob, P., 3rd, Hsieh, J., and Faix, D. (1994) Effects of cigarette smoking and its cessation on lipid metabolism and energy expenditure in heavy smokers. J. Clin. InVest. 93, 265–272. (33) Aoshiba, K., Yasui, S., Nishimura, K., and Nagai, A. (1999) Thiol depletion induces apoptosis in cultured lung fibroblasts. Am. J. Respir. Cell Mol. Biol. 21, 54–64. (34) Chow, C. K. (1993) Cigarette smoking and oxidative damage in the lung. Ann. N. Y. Acad. Sci. 686, 289–298. (35) Hoshino, Y., Mio, T., Nagai, S., Miki, H., Ito, I., and Izumi, T. (2001) Cytotoxic effects of cigarette smoke extract on an alveolar type II cell-derived cell line. Am. J. Physiol. Lung Cell Mol. Physiol. 281, L509–L516. (36) Ramage, L., Jones, A. C., and Whelan, C. J. (2006) Induction of apoptosis with tobacco smoke and related products in A549 lung epithelial cells in vitro. J. Inflammation (London, U. K.) 3, 3. (37) Pawliczak, R., Huang, X. L., Nanavaty, U. B., Lawrence, M., Madara, P., and Shelhamer, J. H. (2002) Oxidative stress induces arachidonate release from human lung cells through the epithelial growth factor receptor pathway. Am. J. Respir. Cell Mol. Biol. 27, 722–731. (38) Leonardi, R., Zhang, Y. M., Rock, C. O., and Jackowski, S. (2005) Coenzyme A: back in action. Prog. Lipid Res. 44, 125–153. (39) Kamp, D. W., Srinivasan, M., and Weitzman, S. A. (2001) Cigarette smoke and asbestos activate poly-ADP-ribose polymerase in alveolar epithelial cells. J. InVest. Med. 49, 68–76.

TX8003246

Effects of Mainstream Cigarette Smoke on the Global Metabolome of

Recommend Documents