Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS

Abstract

Introduction

Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventional analytical techniques.

Objectives

This study aimed to develop a new high throughput method based on metabolomics able to detect a wide range of metabolites classes in Elaeis guineensis leaves. Furthermore, we investigate the effects caused by harvesting/sample preparation steps for the metabolites identification.

Method

Metabolites analyses were performed by ultra-high liquid chromatography—mass spectrometry (UHPLC–MS) using both ionization modes, ESI(+)–MS and ESI(−)–MS. ANOVA simultaneous component analysis (ASCA) of the resulting complex multivariate dataset was applied to evaluate metabolic alterations. Identification of major metabolites was performed by high resolution mass spectrometry and MS/MS experiments.

Result

A high throughput method based on UHPLC–MS was successfully developed to E. guineensis leaves, detecting from polar to non-polar acid and basic metabolites. According to ASCA, oil palm leaves metabolic fingerprintings have shown influence of transportation/storage and extraction solvent used chosen. In fact, the most significant effect is due to the solvent composition. A total of thirteen metabolites were assigned based on HRMS and MS/MS experiments. However, only seven metabolites identified were previously reported, which represents a potential field to discover new metabolites.

Conclusion

Sample preparation steps should be carefully performed in metabolomics studies, because metabolites will be extracted and identified based on transport and solvent of extraction conditions. In this study, we established a reliable analytical protocol, from sample preparation to data analyses, to prospect new metabolites in oil palm leaves. This protocol could be further applied to similar oil-bearing crops.

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References

  1. Abdelnur, P., Caldana, C., & Martins, M. (2014). Metabolomics applied in bioenergy. Chemical and Biological Technologies in Agriculture, 1, 1–22.

    Article  Google Scholar 

  2. Acevedo, J. C., Hernández, J. A., Valdés, C. F., & Khanal, S. K. (2015). Analysis of operating costs for producing biodiesel from oil palm oil at pilot-scale in Colombia. Bioresource Technology, 188, 117–123.

    CAS  Article  PubMed  Google Scholar 

  3. Bourgis, F., Kilaru, A., Ngando-Ebongue, G.-F., Drira, N., Ohrogge, J. B., & Arondel, V. (2011). Comparative transcriptome and metabolite analysis of oil palm and date palm mesocarp that differ dramatically in carbon partitioning. Proceedings of the National Academy of Sciences of the USA, 108(30), 12527–12532.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Dias, D. A., Urban, S., & Roessner, U. (2012). A historical overview of natural products in drug discovery. Metabolites, 2(2), 303–336.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. Fiehn, O. (2001). Combining genomics, metabolome analysis and biochemical modelling to understand metabolic networks. Comparative and Functional Genomics, 2, 155–168.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. Gruca, M., Blach-Overgaard, A., & Balslev, H. (2015). African palm ethno-medicine. Journal of Ethnopharmacology, 165, 227–237.

    Article  PubMed  Google Scholar 

  7. Han, N. M., & May, C. Y. (2010). Determination of antioxidants in oil palm leaves (E. guineensis). American Journal of Applied Science, 7, 1243–1247.

    CAS  Article  Google Scholar 

  8. Jaffri, J. M., Mohamed, S., Ahmad, I. N., et al. (2011a). Effects of catechin-rich oil palm leaf extract on normal and hypertensive rats´ kidney and liver. Food Chemistry, 128, 433–441.

    CAS  Article  PubMed  Google Scholar 

  9. Jaffri, J. M., Mohamed, S., Rohimi, N., et al. (2011b). Antihypertensive and cardiovascular effects of catechin-rich oil palm (E. guineensis) leaf extract in nitric oxide-deficient rats. Journal of Medicinal Food, 14, 775–783.

    CAS  Article  PubMed  Google Scholar 

  10. Kind, T., & Fiehn, O. (2010). Advances in structure elucidation of small molecules using mass spectrometry. Bioanalytical Reviews, 2(1–4), 23–60.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Lei, Z., Huhman, V., & Sumner, W. (2011). Mass spectrometry strategies in metabolomics. Journal of Biology and Chemistry, 286, 25435–25442.

    CAS  Article  Google Scholar 

  12. Lidaa, H. N., Sundrama, K., Siewa, W. L., et al. (2002). TAG composition and solid fat content of palm oil, sunflower oil, and palm kernel olein blends before and after chemical interesterification. Journal of the American Oil Chemists Society, 79(11), 1137–1144.

    Article  Google Scholar 

  13. Ngando-Ebongue, G. F., Dhouib, R., Carrière, F., et al. (2006). Assaying lipase activity from oil palm fruit (E. guineensis Jaq.) mesocarp. Plant Physiology and Biochemistry, 44, 611–617.

    CAS  Article  PubMed  Google Scholar 

  14. Núñez, O., Gallart-Ayala, H., Martins, C. P. B., et al. (2013). State-of-the-art in fast liquid chromatography for bio-analytical applications. Journal of Chromatography B, 927, 3–21.

    Article  Google Scholar 

  15. Philosoph-Hadas, S., Meir, S., Akiri, B., & Kanner, J. (1994). Oxidative defense systems in leaves of three edible herb species in relation to their senescence rates. Journal of Agriculture and Food Chemistry, 42(11), 2376–2381.

    CAS  Article  Google Scholar 

  16. Putri, A. P., & Fukusaki, E. (2014). Mass spectrometry-based metabolomics—A practical guide. Boca Raton: CRC Press.

    Google Scholar 

  17. Rajavel, V., Sattar, M. Z. A., Abdulla, M. A., et al. (2012). Chronic administration of oil palm (E. guineensis) leaves extract attenuates hyperglycaemic-induced oxidative stress and improves renal histopathology and function in experimental diabetes. Evidence-Based Complementary and Alternative Medicine, 2012(195367), 12.

    Google Scholar 

  18. Rodrigues, M. D. R. L., Amblard, P., Barcelos, E., et al. (2006). Avaliação do estado nutricional do dendezeiro: análise foliar (reformulada).

  19. Rosalina Tan, R. T., Mohamed, S., Samaneh, G. F., et al. (2011). Polyphenol rich oil palm leaves extract reduce hyperglycaemia and lipid oxidation in STZ-rats. International Food Research Journal, 18, 179–188.

    CAS  Google Scholar 

  20. Smilde, A. K., Jansen, J. J., Hoefsloot, H. C. J., et al. (2005). ANOVA-simultaneous component analysis (ASCA): A new tool for analyzing designed metabolomics data. Bioinformatics, 21(13), 3043–3048.

    CAS  Article  PubMed  Google Scholar 

  21. Tahir, N. I., Shaari, K., Abas, F., et al. (2012). Characterization of apigenin and luteolin derivates form oil palm (E. guineensis Jacq.) leaf using LC–ESI-MS/MS. Journal of Agriculture and Food Chemistry, 60(45), 11201–11210.

    CAS  Article  Google Scholar 

  22. Tahir, N. I., Shaari, K., Abas, F., et al. (2013). Identification of oil palm (E. guineensis) spear leaf metabolites using mass spectrometry and neutral loss analysis. Journal of Oil Palm Research, 25(1), 72–83.

    CAS  Google Scholar 

  23. Varatharajan, R., Sattar, M. Z. A., Chung, I., et al. (2013). Antioxidant and pro-oxidant effects of oil palm (E. guineensis) leaves extract in experimental diabetic nephropathy. BMC Complementary and Alternative Medicine, 13, 242.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Verheye, W. (Ed.). (2010). Growth and production of oil palm. Encyclopedia of life support systems. Oxford: EOLSS.

    Google Scholar 

  25. Wu, H., Guo, J., Chen, S., Liu, X., Zhou, Y., Zhang, X., et al. (2013). Recent developments in qualitative and quantitative analysis of phytochemical constituents and their metabolites using liquid chromatography–mass spectrometry—review. Journal of Pharmaceutical and Biomedical Analysis, 72, 267–291.

    CAS  Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thanks The Brazilian Agricultural Research Corporation (EMBRAPA), The Federal Foundation for the Brazilian Research and Development (FINEP), Coordination for the Improvement of Higher Education Personnel (CAPES) and National Council for Scientific and Technological Development (CNPQ) for the financial support. The authors thank Daniel Nogoceke Sifuentes for his technical support.

Funding

This study was funded by FINEP — Project “DENDEPALM—Estratégias genômicas e agregação de valor para a cadeia produtiva do dendê” (Grant Number 0 1 13 0315 00).

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Correspondence to Patrícia Verardi Abdelnur.

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Luiz Henrique Galli Vargas, José Antônio de Aquino Ribeiro, Jorge Candido Rodrigues Neto, Maria Esther Ricci-Silva, Manoel Teixeira de Souza Júnior, Clenilson Martins Rodrigues, Anselmo Elcana de Oliveira and Patrícia Verardi Abdelnur declare that they have no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Luiz Henrique Galli Vargas and Jorge Candido Rodrigues Neto have contributed equally to this manuscript.

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Vargas, L.H.G., Neto, J.C.R., de Aquino Ribeiro, J.A. et al. Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS. Metabolomics 12, 153 (2016). https://doi.org/10.1007/s11306-016-1100-z

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Keywords

  • Untargeted metabolomics
  • Bioprospection
  • Metabolite identification
  • Mass Spectrometry
  • High throughput analysis
  • Oil-bearing crop