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. 2015 Nov 4;10(11):e0142053.
doi: 10.1371/journal.pone.0142053. eCollection 2015.

E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells

Affiliations

E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells

Argo Aug et al. PLoS One. .

Abstract

E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC) and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL) on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC) with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1) to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1's maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Principal component analysis of the metabolic state of primary normal human bronchial epithelial cells cultivated in air-liquid interface after exposure to (A) e-cigarette liquid (ECL) (100 μM by nicotine) and (B) 10 μg/mL cigarette smoke condensate (CSC) (black solid lines).
The time points at the arrow turns are 1, 2, 5, 7, and 13 h. Long dashes: Addition of 10 μM O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine to the cells having been exposed to ECL for 1 h (the arrow starts at 2 h time point), short dashes: Addition of 2 mM N-acetylcysteine to the cells having been exposed to ECL for 1 h (the arrow starts at 2 h time point). For each treatment and for any time point, n = 3 (gray circles). Error bars indicate standard errors of means. PComp1 and PComp2 are the two principal components describing the highest fraction of the effect of cells’ metabolome.
Fig 2
Fig 2. Mass spectrum of primary normal human bronchial epithelial cells cultivated in air-liquid interface after exposure to e-cigarette liquid (ECL) (100 μM by nicotine) and 10 μg/mL cigarette smoke condensate (CSC) consisting of 1,822 distinct mass-to-charge signals.
The figure represents the proportions of the spectrum that were significantly (p<0.05) affected by addition of ECL (392 signals) or CSC (569 signals) during the first 7 h. There were 138 signals that were significantly affected by both stimuli.
Fig 3
Fig 3. Time dynamics of the expression of the metabolites of primary normal human bronchial epithelial cells (HBEC) cultured in air-liquid interface being affected by e-cigarette liquid (ECL) (100 μM by nicotine) (black lines) and 10 μg/mL cigarette smoke condensate (CSC) (grey lines) for 13 h.
Solid lines: HBEC treated with ECL (solid black lines) or with CSC (solid grey lines). Long black dashes: HBEC treated with ECL and 10 μM O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1) (added at 1h). Long grey dashes: HBEC treated with CSC and 10 μM UPF1 (added at 1h). Short black dashes: HBEC treated with ECL and 2 mM N-acetylcysteine (NAC) (added at 1h). Short grey dashes: HBEC treated with CSC and 2 mM NAC (added at 1h). For each treatment and for any time point, n = 3. Error bars indicate standard errors of means. (A) arginine ([M+H]+ = 175); (B) adenosine diphosphate ([M-H]- = 426); (C) phosphatidylcholine (18:0/20:4) ([M+H]+ = 811); (D) α-ketoglutarate ([M-H]- = 145). *p < 0.05, ECL-exposed cells versus untreated cells; #p < 0.05, ECL- and UPF1-exposed cells versus untreated cells; ^p < 0.05, ECL- and NAC-exposed cells versus untreated cells; ¤p < 0.05, CSC-exposed cells versus untreated cells; ~p < 0.05, CSC- and UPF1-exposed cells versus untreated cells; “p < 0.05, CSC- and NAC-exposed cells versus untreated cells.

References

    1. Harrell PT, Marquinez NS, Correa JB, Meltzer LR, Unrod M, Sutton SK, et al. Expectancies for Cigarettes, E-Cigarettes, and Nicotine Replacement Therapies Among E-cigarette Users ("Vapers"). Nicotine Tob Res. 2014. Epub 2014/08/30. doi: ntu149 [pii] 10.1093/ntr/ntu149 . - DOI - PMC - PubMed
    1. Cobb NK, Abrams DB. E-cigarette or drug-delivery device? Regulating novel nicotine products. N Engl J Med. 2011;365(3):193–5. Epub 2011/07/22. 10.1056/NEJMp1105249 . - DOI - PubMed
    1. Zhu SH, Sun JY, Bonnevie E, Cummins SE, Gamst A, Yin L, et al. Four hundred and sixty brands of e-cigarettes and counting: implications for product regulation. Tob Control. 2014;23 Suppl 3:iii3-9. Epub 2014/06/18. doi: tobaccocontrol-2014-051670 [pii] 10.1136/tobaccocontrol-2014-051670 - DOI - PMC - PubMed
    1. Pokhrel P, Fagan P, Little MA, Kawamoto CT, Herzog TA. Smokers who try e-cigarettes to quit smoking: findings from a multiethnic study in Hawaii. Am J Public Health. 2013;103(9):e57–62. Epub 2013/07/20. 10.2105/AJPH.2013.301453 - DOI - PMC - PubMed
    1. Polosa R, Caponnetto P, Morjaria JB, Papale G, Campagna D, Russo C. Effect of an electronic nicotine delivery device (e-Cigarette) on smoking reduction and cessation: a prospective 6-month pilot study. BMC Public Health. 2011;11:786. Epub 2011/10/13. doi: 1471-2458-11-786 [pii] 10.1186/1471-2458-11-786 - DOI - PMC - PubMed

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