Advertisement

Environmental Science and Pollution Research

, Volume 25, Issue 31, pp 31656–31665 | Cite as

Nuclear magnetic resonance-based metabolomic investigation reveals metabolic perturbations in PM2.5-treated A549 cells

  • Dacheng Huang
  • Yajuan Zou
  • Anees Abbas
  • Bona Dai
Research Article

Abstract

Exposure to PM2.5 is associated with an increased risk of lung diseases, and oxidative damage is the main reason for PM2.5-mediated lung injuries. However, little is known about the early molecular events in PM2.5-induced lung toxicity. In the present study, the metabolites in PM2.5-treated A549 cells were examined via a robust and nondestructive nuclear magnetic resonance (NMR)-based metabolic approach to clarify the molecular mechanism of PM2.5-induced toxicity. NMR analysis revealed that 12 metabolites were significantly altered in PM2.5-treated A549 cells, including up-regulation of alanine, valine, lactate, ω-6 fatty acids, and citrate and decreased levels of gamma-aminobutyric acid, acetate, leucine, isoleucine, D-glucose, lysine, and dimethylglycine. Pathway analysis demonstrated that seven metabolic pathways which included alanine, aspartate and glutamate metabolism, aminoacyl-tRNA biosynthesis, taurine and hypotaurine metabolism, arginine and proline metabolism, starch and sucrose metabolism, valine, leucine and isoleucine biosynthesis, and tricarboxylic acid cycle were mostly influenced. Our results indicate that NMR technique turns out to be a simple and reliable method for exploring the toxicity mechanism of air pollutant.

Keywords

PM2.5 A549 cells Lung toxicity Nuclear magnetic resonance Metabolite Metabolism pathway 

Notes

Acknowledgments

We appreciate Dr. Li Xu for her critical comments on the metabolite pathway analysis.

Funding information

Funds were from the Shanghai Science and Technology Committee (17030501400) and the National Natural Science Foundation of China (51501109).

References

  1. Adams K, Greenbaum D, Shaikh R, Erp A, Russell A (2015) Particulate matter components, sources, and health: systematic approaches to testing effects. J Air Waste Manag Assoc 65(5):544–558CrossRefGoogle Scholar
  2. Calcabrini A, Meschini S, Marra M, Falzano L, Colone M, Berardis B, Paoletti L, Arancia G, Fiorentini C (2004) Fine environmental particulate engenders alterations in human lung epithelial A549 cells. Environ Res 95:82–91CrossRefGoogle Scholar
  3. Deng X, Zhang F, Rui W, Long F, Wang L, Feng Z, Chen D, Ding W (2013) PM2.5-induced oxidative stress triggers autophagy in human lung epithelial A549 cells. Toxicol In Vitro 27:1762–1770CrossRefGoogle Scholar
  4. Dergham M, Lepers C, Verdin A, Billet S, Cazier F, Courcot D, Shirali P, Garçon G (2012) Prooxidant and proinflammatory potency of air pollution particulate matter (PM2.5–0.3) produced in rural, urban, or industrial surroundings in human bronchial epithelial cells (BEAS-2B). Chem Res Toxicol 25(4):904–919CrossRefGoogle Scholar
  5. Duarte I, Diaz S, Gil A (2014) NMR metabolomics of human blood and urine in disease research. J Pharm Biomed Anal 93:17–26CrossRefGoogle Scholar
  6. Hu J, Rommereim D, Minard K, Woodstock A, Harrer B, Wind R, Phipps R, Sime P (2008) Metabolomics in lung inflammation: a high-resolution 1H NMR study of mice exposed to silica dust. Toxicol Mech Methods 18:385–398CrossRefGoogle Scholar
  7. Hu J, Zhang H, Chen S, Ying Q, Wiedinmyer C, Vandenberghe F, Kleeman M (2014) Identifying PM2.5 and PM0.1 sources for epidemiological studies in California. Environ Sci Technol 48:4980–4990CrossRefGoogle Scholar
  8. Huang Q, Zhang J, Luo L, Wang X, Wang X, Alamdar A, Peng S, Liu L, Tian M, Shen H (2015) Metabolomics reveals disturbed metabolic pathways in human lung epithelial cells exposed to airborne fine particulate matter. Toxicol Res 4:939–947CrossRefGoogle Scholar
  9. Huo T, Fang Y, Zhao L, Xiong Z, Zhang Y, Wang Y, Feng C, Yuan M, Wang S, Chen M, Jiang H (2016) 1HNMR-based metabonomic study of sub-chronic hepatotoxicity induced by realgar. J Ethnopharmacol 192:1–9CrossRefGoogle Scholar
  10. Jouret F, Leenders J, Poma L, Defraigne J, Krzesinski J, Tullio P (2016) Nuclear magnetic resonance metabolomic profiling of mouse kidney, urine and serum following renal ischemia/reperfusion injury. PLoS One 11(9):e0163021CrossRefGoogle Scholar
  11. Kampa M, Castanas E (2008) Human health effects of air pollution. Environ Pollut 151:362–367CrossRefGoogle Scholar
  12. Kelly F, Fussell J (2012) Size, source and chemical composition as determinants of toxicity attributable to ambient particulate matter. Atmos Environ 60:504–526CrossRefGoogle Scholar
  13. Kim K, Kabir E, Kabir S (2015) A review on the human health impact of airborne particulate matter. Environ Int 74:136–143CrossRefGoogle Scholar
  14. Lam T, Gutierrez-Juarez R, Pocai A, Rossetti L (2005) Regulation of blood glucose by hypothalamic pyruvate metabolism. Science 309(5736):943–947CrossRefGoogle Scholar
  15. Lankadurai B, Nagato E, Simpson M (2013) Environmental metabolomics: an emerging approach to study organism responses to environmental stressors. Environ Rev 21:180–205CrossRefGoogle Scholar
  16. Lanza IR, Zhang S, Ward LE, Karakelides H, Raftery D, Nair KS (2010) Quantitative metabolomics by 1H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes. PLoS One 5(5):e10538CrossRefGoogle Scholar
  17. Li R, Kou X, Geng H, Xie J, Yang Z, Zhang Y, Cai Z, Dong C (2015) Effect of ambient PM2.5 on lung mitochondrial damage and fusion/fission gene expression in rats. Chem Res Toxicol 28(3):408–418CrossRefGoogle Scholar
  18. Liang L, Engling G, Zhang X, Sun J, Zhang Y, Xu W, Liu C, Zhang G, Liu X, Ma Q (2017) Chemical characteristics of PM2.5 during summer at a background site of the Yangtze River Delta in China. Atmos Res 198:163–172CrossRefGoogle Scholar
  19. Lin C, Wu S, Liang H, Liu Y, Ueng T (2014) Metabolomic analysis of the effects of motorcycle exhaust on rat testes and liver. Aerosol Air Qual Res 14:1714–1725CrossRefGoogle Scholar
  20. Liu Y (2006) Fatty acid oxidation is a dominant bioenergetic pathway in prostate cancer. Prostate Cancer Prostatic Dis 9:230–234CrossRefGoogle Scholar
  21. Markley J, Bruschweiler R, Edison A, Eghbalnia H, Powers R, Raftery D, Wishart D (2017) The future of NMR-based metabolomics. Curr Opin Biol 43:34–40CrossRefGoogle Scholar
  22. Nemmar A, Holme J, Rosas I, Schwarze P, Alfaro-Moreno E (2013) Recent advances in particulate matter and nanoparticle toxicology: a review of the in vivo and in vitro studies. Biomed Res Int 2013:1–22.  https://doi.org/10.1155/2013/279371 CrossRefGoogle Scholar
  23. Park S, Kim Y, Kang C (2002) Atmospheric polycyclic aromatic hydrocarbons in Seoul. Korea Atmos Environ 36:2917–2924CrossRefGoogle Scholar
  24. Pui D, Chen S, Zuo Z (2014) PM2.5 in China: measurements, sources, visibility and health effects, and mitigation. Particuology 13:1–26CrossRefGoogle Scholar
  25. Schönfeld P, Wojtczak L (2016) Short- and medium-chain fatty acids in energy metabolism: the cellular perspective. J Lipid Res 57:943–954CrossRefGoogle Scholar
  26. Simón-Manso Y, Lowenthal M, Kilpatrick L, Sampson M, Telu K, Rudnick P, Mallard W, Bearden D, Schock T, Tchekhovskoi D, Blonder N, Yan X, Liang Y, Zheng Y, Wallace W, Neta P, Phinney K, Remaley A, Stein S (2013) Metabolite profiling of a NIST standard reference material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources. Anal Chem 85:11725–11731CrossRefGoogle Scholar
  27. Wang J, Hu Z, Chen Y, Chen Z, Xu S (2013a) Contamination characteristics and possible sources of PM10 and PM2.5 in different functional areas of Shanghai, China. Atmos Environ 68:221–229CrossRefGoogle Scholar
  28. Wang L, Tang Y, Liu S, Mao S, Ling Y, Liu D, He X, Wang X (2013b) Metabonomic profiling of serum and urine by 1H NMR-based spectroscopy discriminates patients with chronic obstructive pulmonary disease and healthy individuals. PLoS One 8(6):e65675CrossRefGoogle Scholar
  29. Wang W, Wu Z, Dai Z, Yang Y, Wang J, Wu G (2013c) Glycine metabolism in animals and humans: implications for nutrition and health. Amino Acids 45:463–477CrossRefGoogle Scholar
  30. Wang Z, Zheng Y, Zhao B, Zhang Y, Liu Z, Xu J, Chen Y, Yang Z, Wang F, Wang H, He J, Zhang R, Abliz Z (2015) Human metabolic responses to chronic environmental polycyclic aromatic hydrocarbon exposure by a metabolomic approach. J Proteome Res 14:2583–2593CrossRefGoogle Scholar
  31. Wei Y, Wang Z, Chang C, Fan T, Su L, Chen F (2013) Global metabolomic profiling reveals an association of metal fume exposure and plasma unsaturated fatty acids. PLoS One 8(10):77413–77422CrossRefGoogle Scholar
  32. Wohlt J, Clark J, Derrig R, Davis C (1977) Valine, leucine, and isoleucine metabolism by lactating bovine mammary tissue. J Dairy Sci 12(60):1875–1882CrossRefGoogle Scholar
  33. Xia J, Sinelnikov I, Han B, Wishart D (2015) MetaboAnalyst 3.0—making metabolomics more meaningful. Nucleic Acids Res 43(W1):W251–W257.  https://doi.org/10.1093/nar/gkv380 CrossRefGoogle Scholar
  34. Zou Y, Jin C, Su Y, Li J, Zhu B (2016) Water soluble and insoluble components of urban PM2.5 and their cytotoxic effects on epithelial cells (A549) in vitro. Environ Pollut 212:627–635CrossRefGoogle Scholar
  35. Zou Y, Wu Y, Wang Y, Li Y, Jin C (2017) Physicochemical properties, in vitro cytotoxic and genotoxic effects of PM1.0 and PM2.5 from Shanghai, China. Environ Sci Pollut Res 24:19508–19516CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Dacheng Huang
    • 1
  • Yajuan Zou
    • 2
  • Anees Abbas
    • 3
  • Bona Dai
    • 2
  1. 1.Engineering CenterShanghai University of Engineering and ScienceShanghaiChina
  2. 2.Instrumental Analysis CenterShanghai Jiao Tong UniversityShanghaiChina
  3. 3.School of Chemistry and Chemical EngineeringShanghai Jiao Tong UniversityShanghaiChina

Personalised recommendations