, Volume 10, Issue 5, pp 805–815 | Cite as

Study of polar metabolites in tobacco from different geographical origins by using capillary electrophoresis–mass spectrometry

  • Jieyu Zhao
  • Chunxiu Hu
  • Jun Zeng
  • Yanni Zhao
  • Junjie Zhang
  • Yuwei Chang
  • Lili Li
  • Chunxia Zhao
  • Xin Lu
  • Guowang XuEmail author
Original Article


Many metabolites in plant are highly polar and ionic. Their analysis using gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry can be problematic. Therefore a capillary electrophoresis–mass spectrometry (CE–MS) method with charge-driven separation characteristic was developed to investigate polar metabolites in tobacco. To obtain as many features as possible, extraction of polar metabolites was optimized by the design of experiments and evaluated by univariate statistics. Method validation was carried out to evaluate the analytical characteristics including calibration curve, precision, sample stability and extraction reproducibility. The developed method was successfully applied in studying 30 tobacco leaves obtained from Yunnan and Guizhou provinces in China. A total of 154 polar metabolites were identified based on available database. Multivariate pattern recognition clearly revealed the metabolic differences between the two geographic areas and 43 significantly different metabolites were defined by the non-parametric hypothesis test (Mann–Whitney U test) and false discovery rate. Some key metabolites involved in photosynthesis such as ribulose 1,5-disphosphate, fructose 1,6-diphosphate, glycine, betaine, GABA and serine were found to be susceptible to environmental conditions. This study shows that the metabolic profiling based on CE–MS can clearly discriminate tobacco leaves of different geographical origins and understand the relationship between plant metabolites and their geographical origins.


Capillary electrophoresis Mass spectrometry Plant metabolomics Method validation Tobacco leaf 

Supplementary material

11306_2014_631_MOESM1_ESM.docx (738 kb)
Supplementary material 1 (DOCX 738 kb)


  1. Alan, M. K., & Frank, J. T. (2000). Gamma aminobutyric acid (GABA) and plant responses to stress. Critical Reviews in Plant Sciences, 19(6), 479–509.CrossRefGoogle Scholar
  2. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.Google Scholar
  3. Benjamini, Y., & Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics, 29(4), 1165–1188.CrossRefGoogle Scholar
  4. Bligh, E. G., & Dyer, W. J. (1959). A rapid method of total lipid extraction and purification. Canadian Journal of Biochemistry and Physiology, 37(8), 911–917.CrossRefPubMedGoogle Scholar
  5. Bouché, N., & Fromm, H. (2004). GABA in plants: Just a metabolite? Trends in Plant Science, 9(3), 110–115.CrossRefPubMedGoogle Scholar
  6. Cazier, J. B., Kaisaki, P. J., Argoud, K., Blaise, B. J., Veselkov, K., Ebbels, T. M., et al. (2011). Untargeted metabolome quantitative trait locus mapping associates variation in urine glycerate to mutant glycerate kinase. Journal of Proteome Research, 11(2), 631–642.CrossRefPubMedGoogle Scholar
  7. Cruz, J. A., Emery, C., Wüst, M., Kramer, D. M., & Lange, B. M. (2008). Metabolite profiling of Calvin cycle intermediates by HPLC-MS using mixed-mode stationary phases. The Plant Journal: For Cell and Molecular Biology, 55(6), 1047–1060.CrossRefGoogle Scholar
  8. De Vos, R. C., Moco, S., Lommen, A., Keurentjes, J. J., Bino, R. J., & Hall, R. D. (2007). Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nature Protocols, 2(4), 778–791.CrossRefPubMedGoogle Scholar
  9. Decaestecker, T. N., Lambert, W. E., Van Peteghem, C. H., Deforce, D., & Van Bocxlaer, J. F. (2004). Optimization of solid-phase extraction for a liquid chromatographic–tandem mass spectrometric general unknown screening procedure by means of computational techniques. Journal of Chromatography A, 1056(1–2), 57–65.CrossRefPubMedGoogle Scholar
  10. Ferreira, S. L., Bruns, R. E., da Silva, E. G., Dos Santos, W. N., Quintella, C. M., David, J. M., et al. (2007). Statistical designs and response surface techniques for the optimization of chromatographic systems. Journal of Chromatography A, 1158(1–2), 2–14.CrossRefPubMedGoogle Scholar
  11. Fiehn, O., Kopka, J., Trethewey, R. N., & Willmitzer, L. (2000a). Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Analytical Chemistry, 72(15), 3573–3580.CrossRefPubMedGoogle Scholar
  12. Fiehn, O., Kopka, J., Dörmann, P., Altmann, T., Trethewey, R. N., & Willmitzer, L. (2000b). Metabolite profiling for plant functional genomics. Nature Biotechnology, 18(11), 1157–1161.CrossRefPubMedGoogle Scholar
  13. Foyer, C. H., Parry, M., & Noctor, G. (2003). Markers and signals associated with nitrogen assimilation in higher plants. Journal of Experimental Botany, 54(382), 585–593.CrossRefPubMedGoogle Scholar
  14. Fraser, K., Harrison, S. J., Lane, G. A., Otte, D. E., Hemar, Y., Quek, S. Y., et al. (2012). Non-targeted analysis of tea by hydrophilic interaction liquid chromatography and high resolution mass spectrometry. Food Chemistry, 134(3), 1616–1623.CrossRefPubMedGoogle Scholar
  15. Gao, W., Yang, H., Qi, L. W., Liu, E. H., Ren, M. T., Yan, Y. T., et al. (2012). Unbiased metabolite profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis for herbal authentication: Classification of seven Lonicera species flower buds. Journal of Chromatography A, 1245, 109–116.CrossRefPubMedGoogle Scholar
  16. Garcia, L. M. Z., de Oliveira, T. F., Soares, P. K., Bruns, R. E., & Scarminio, I. S. (2010). Statistical mixture design—principal component determination of synergic solvent interactions for natural product extractions. Chemometrics and Intelligent Laboratory Systems, 103(1), 1–7.CrossRefGoogle Scholar
  17. Gullberg, J., Jonsson, P., Nordström, A., Sjöström, M., & Moritz, T. (2004). Design of experiments: An efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry. Anaytical Biochemistry, 331(2), 283–295.CrossRefGoogle Scholar
  18. Hasunuma, T., Harada, K., Miyazawa, S., Kondo, A., Fukusaki, E., & Miyake, C. (2010). Metabolic turnover analysis by a combination of in vivo 13C-labelling from 13CO2 and metabolic profiling with CE–MS/MS reveals rate-limiting steps of the C3 photosynthetic pathway in Nicotiana tabacum leaves. Journal of Experimental Botany, 61(4), 1041–1051.CrossRefPubMedGoogle Scholar
  19. Hirayama, A., Kami, K., Suqimoto, M., Suqawara, M., Toki, N., Onozuka, H., et al. (2009). Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry. Cancer Research, 69(11), 4918–4925.CrossRefPubMedGoogle Scholar
  20. Holmström, K. O., Somersalo, S., Mandal, A., Palva, T. E., & Welin, B. (2000). Improved tolerance to salinity and low temperature in transgenic tobacco producing glycine betaine. Journal of Experimental Botany, 51(343), 177–185.CrossRefPubMedGoogle Scholar
  21. Krapp, A., Quick, W. P., & Stitt, M. (1991). Ribulose—1,5-bisphosphate carbo xylase-oxygenase, other Calvin-cycle enzymes, and chlorophyll decrease when glucose is supplied to mature spinach leaves via the transpiration stream. Planta, 186(1), 58–69.CrossRefPubMedGoogle Scholar
  22. Leffingwell, J. C. (1999). Leaf chemistry: Basic chemical constituents of tobacco leaf and differences among tobacco type. In D. L. Davis & M. T. Nielsen (Eds.), Tobacco: Production, chemistry and technology (pp. 304–312). Oxford: Blackwell Science.Google Scholar
  23. Levandi, T., Leon, C., Kaljurand, M., Garcia-Cañas, V., & Cifuentes, A. (2008). Capillary electrophoresis time-of-flight mass spectrometry for comparative metabolomics of transgenic versus conventional maize. Analytical Chemistry, 80(16), 6329–6335.CrossRefPubMedGoogle Scholar
  24. Li, X., Xu, Z., Lu, X., Yang, X., Yin, P., Kong, H., et al. (2009). Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry for metabonomics: Biomarker discovery for diabetes mellitus. Analytica Chimica Acta, 633(2), 257–262.CrossRefPubMedGoogle Scholar
  25. Li, Y., Pang, T., Li, Y., Wang, X., Li, Q., Lu, X., et al. (2011). Gas chromatography-mass spectrometric method for metabolic profiling of tobacco leaves. Journal of Separation Science, 34(12), 1447–1454.CrossRefPubMedGoogle Scholar
  26. Masson, P., Alves, A. C., Ebbels, T. M., Nicholson, J. K., & Want, E. J. (2010). Optimization and evaluation of metabolite extraction protocols for untargeted metabolic profiling of liver samples by UPLC-MS. Analytical Chemistry, 82(18), 7779–7786.CrossRefPubMedGoogle Scholar
  27. Pang, T., Bai, C., Xu, Y., Xu, G., Yuan, Z., Su, Y., et al. (2006). Determination of sugars in tobacco leaf by HPLC with evaporative light scattering detection. Journal of Liquid Chromatography & Related Technologies, 29(9), 1281–1289.CrossRefGoogle Scholar
  28. Ramautar, R., Somsen, G. W., & de Jong, G. J. (2009). CE–MS in metabolomics. Electrophoresis, 30(1), 276–291.CrossRefPubMedGoogle Scholar
  29. Ramautar, R., Somsen, G. W., & de Jong, G. J. (2013). CE–MS for metabolomics: Developments and applications in the period 2010–2012. Electrophoresis, 34(1), 86–98.CrossRefPubMedGoogle Scholar
  30. Riedelsheimer, C., Lisec, J., Czedik-Eysenberg, A., Sulpice, R., Flis, A., Grieder, C., et al. (2012). Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize. Proceedings of the National Academy of Sciences, 109(23), 8872–8877.CrossRefGoogle Scholar
  31. Rodgers, J. L., & Nicewander, W. A. (1988). Thirteen ways to look at the correlation coefficient. The American Statistician, 42(1), 59–66.CrossRefGoogle Scholar
  32. Rodríguez, R., Mañes, J., & Picó, Y. (2003). Off-Line solid-phase microextraction and capillary electrophoresis mass spectrometry to determine acidic pesticides in fruits. Analytical Chemistry, 75(3), 452–459.CrossRefPubMedGoogle Scholar
  33. Saric, J., Want, E. J., Duthaler, U., Lewis, M., Keiser, J., Shockcor, J. P., et al. (2012). Systematic evaluation of extraction methods for multiplatform-based metabotyping: application to the fasciola hepatica metabolome. Analytical Chemistry, 84(16), 6963–6972.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Sato, S., Soga, T., Nishioka, T., & Tomita, M. (2004). Simultaneous determination of the main metabolites in rice leaves using capillary electrophoresis mass spectrometry and capillary electrophoresis diode array detection. The Plant Jounal, 40(1), 151–163.CrossRefGoogle Scholar
  35. Scherling, C., Roscher, C., Giavalisco, P., Schulze, E.-D., & Weckwerth, W. (2010). Metabolomics unravel contrasting effects of biodiversity on the performance of individual plant species. PLoS ONE,. doi: 10.1371/journal.pone.0012569.PubMedPubMedCentralGoogle Scholar
  36. Shulaev, V., Cortes, D., Miller, G., & Mittler, R. (2008). Metabolomics for plant stress response. Physiologia Plantarum, 132(2), 199–208.CrossRefPubMedGoogle Scholar
  37. Soga, T. (2000). Amino acid analysis by capillary electrophoresis electrospray ionization mass spectrometry. Analytical Chemistry, 72(6), 1236–1241.CrossRefPubMedGoogle Scholar
  38. Soga, T., Ueno, Y., Naraoka, H., Ohashi, Y., Tomita, M., & Nishioka, T. (2002). Simultaneous determination of anionic intermediates for metabolic pathways by capillary electrophoresis electrospray ionization mass spectrometry. Analytical Chemistry, 74(10), 2233–2239.CrossRefPubMedGoogle Scholar
  39. Soga, T., Ishikawa, T., Igarashi, S., Sugawara, K., Kakazu, Y., & Tomita, M. (2007). Analysis of nucleotides by pressure-assisted capillary electrophoresis–mass spectrometry using silanol mask technique. Journal of Chromatography A, 1159(1–2), 125–133.CrossRefPubMedGoogle Scholar
  40. Soga, T., Igarashi, K., Ito, C., Mizobuchi, K., Zimmermann, H. P., & Tomita, M. (2009). Metabolomic profiling of anionic metabolites by capillary electrophoresis mass spectrometry. Analytical Chemistry, 81(15), 6165–6174.CrossRefPubMedGoogle Scholar
  41. Spagou, K., Wilson, I. D., Masson, P., Theodoridis, G., Raikos, N., Coen, M., et al. (2010). HILIC-UPLC-MS for exploratory urinary metabolic profiling in toxicological studies. Analytical Chemistry, 83(1), 382–390.CrossRefPubMedGoogle Scholar
  42. Stedman, R. L. (1968). Chemical composition of tobacco and tobacco smoke. Chemical Reviews, 68(2), 153–207.CrossRefPubMedGoogle Scholar
  43. Steuer, R., Morgenthal, K., Weckwerth, W., & Selbig, J. (2007). A gentle guide to the analysis of metabolomic data. In W. Weckwerth (Ed.), Metabolomics: Methods and protocols (pp. 105–126). New York: Springer.CrossRefGoogle Scholar
  44. Tawaraya, K., Horie, R., Saito, A., Shinano, T., Wagatsuma, T., Saito, K., et al. (2013). Metabolite profiling of shoot extracts, root extracts, and root exudates of rice plant under phosphorus deficiency. Journal of Plant Nutrition, 36(7), 1138–1159.CrossRefGoogle Scholar
  45. Tikunov, Y., Lommen, A., de Vos, C. H., Verhoeven, H. A., Bino, R. J., Hall, R. D., et al. (2005). A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles. Plant Physiology, 139(3), 1125–1137.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Vuckovic, D., Risticevic, S., & Pawliszyn, J. (2011). In vivo solid-phase microextraction in metabolomics: Opportunities for the direct investigation of biological systems. Angewandte Chemie International Edition, 50(25), 5618–5628.CrossRefPubMedGoogle Scholar
  47. Xiang, G., Yang, H., Yang, L., Zhang, X., Cao, Q., & Miao, M. (2010). Multivariate statistical analysis of tobacco of different origin, grade and variety according to polyphenols and organic acids. Microchemical Journal, 95(2), 198–206.CrossRefGoogle Scholar
  48. Yuliana, N. D., Khatib, A., Verpoorte, R., & Choi, Y. H. (2011). Comprehensive extraction method integrated with NMR metabolomics: A new bioactivity screening method for plants, adenosine A1 receptor binding compounds in orthosiphon stamineus benth. Analytical Chemistry, 83(17), 6902–6906.CrossRefPubMedGoogle Scholar
  49. Zhang, J., Zhang, Y., Du, Y., Chen, S., & Tang, H. (2011). Dynamic metabonomic responses of tobacco (Nicotiana tabacum) plants to salt stress. Journal of Proteome Research, 10(4), 1904–1914.CrossRefPubMedGoogle Scholar
  50. Zhang, L., Wang, X., Guo, J., Xia, Q., Zhao, G., Zhou, H., et al. (2013). Metabolic profiling of Chinese tobacco leaf of different geographical origins by GC-MS. Journal of Agricultural and Food Chemistry, 61(11), 2597–2605.CrossRefPubMedGoogle Scholar
  51. Zhou, T., Xiao, X., & Li, G. (2012). Hybrid field-assisted solid–liquid–solid dispersive extraction for the determination of organochlorine pesticides in tobacco with gas chromatography. Analytical Chemistry, 84(1), 420–427.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Jieyu Zhao
    • 1
  • Chunxiu Hu
    • 1
  • Jun Zeng
    • 1
  • Yanni Zhao
    • 1
  • Junjie Zhang
    • 1
  • Yuwei Chang
    • 1
  • Lili Li
    • 1
  • Chunxia Zhao
    • 1
  • Xin Lu
    • 1
  • Guowang Xu
    • 1
    Email author
  1. 1.Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalianChina

Personalised recommendations