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A simple and efficient method to extract polar metabolites from guar leaves (Cyamopsis tetragonoloba (L.) Taub.) for GC-MS metabolome analysis

https://doi.org/10.18699/VJ19.460

Abstract

Guar (Cyamopsis tetragonoloba (L.) Taub.) is an agricultural crop species new to Russia and is in demand by the gas, oil and food industries. Due to the progress of “omics” technologies and the marker-assisted selection, there is a huge interest in the studies that compare the metabolites of various guar varieties, employing metabolomics as a method of functional genomics. For a large-scale screening of guar germplasm from the VIR collection, it is important to choose an efficient method to extract metabolites from samples. The accuracy of the assessment of the content of metabolites in samples is crucial for distinguishing varieties within the crop, since the metabolome profiles of plants within the same species differ mainly in the quantitative ratio of metabolites, and not in their qualitative composition. In metabolome practice, two methods of extracting polar compounds are usually employed in the preparation of samples for GC-MS analysis. One of the widely used methods of sample preparation is the long-term extraction of metabolites from whole tissues with the aid of a methanol solvent. Another method of sample preparation is based on the short-term methanol extraction of metabolites from frozen and homogenized material. The advantages and disadvantages of these two methods revealed in the course of our work have prompted us to develop a new approach that avoids some difficulties in analyzing the metabolic profiles of leaves of various guar varieties. The method we suggested combines the advantages of the two above-mentioned approaches of sample preparation, namely eliminates the loss of metabolites due to centrifugation and ensures the complete destruction of all cell walls, ensuring the maximum extraction level of polar metabolites. The essence of the new method is that the leaf is rapidly frozen in liquid nitrogen with subsequent thawing in cold methanol. Thus, leaf tissues retain morphological integrity, and subsequent centrifugation, necessary for homogenization, is skipped. We have checked the effectiveness of this improved method by experiments with leaf samples of three guar genotypes. It has been shown that the amount of extracted metabolites increases more than 5-fold compared to extraction with methanol from fresh unfrozen leaf tissues and more than 2-fold compared to extraction with methanol after freezing and homogenization. Extraction of metabolites using the new method allows the GC-MS analysis of guar samples to be conducted with the least loss and high accuracy required to distinguish varieties.

About the Authors

S. B. Teplyakova
Federal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR)
Russian Federation
St. Petersburg


A. L. Shavarda
St. Petersburg State University; Komarov Botanical Institute, RAS
Russian Federation
St. Petersburg


T. V. Shelenga
Federal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR)
Russian Federation
St. Petersburg


E. A. Dzyubenko
Federal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR)
Russian Federation
St. Petersburg


E. K. Potokina
Federal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR); St. Petersburg State University
Russian Federation
St. Petersburg


References

1. Loskutov I.G., Shelenga T.V., Konarev A.V., Shavarda A.L., Blinova E.V., Dzubenko N.I. The metabolomic approach to the comparative analysis of wild and cultivated species of oats (Avena L.). Vavilovskii Zhurnal Genetiki i Selektsii = Vavilov Journal of Genetics and Breeding. 2016;20(5):636-642. DOI 10.18699/VJ16.185. (in Russian)

2. Smolikova G.N., Shavarda A.L., Alekseichuk I.V., Chantseva V.V., Medvedev S.S. The metabolomic approach to the assessment of cultivar specificity of Brassica napus L. seeds. Vavilovskii Zhurnal Genetiki i Selektsii = Vavilov Journal of Genetics and Breeding. 2015; 19(1):121-127. DOI 10.18699/VJ15.015. (in Russian)

3. Alonso A., Marsal S., Julià A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front. Bioeng. Biotechnol. 2015; 3(23):1-20. DOI 10.3389/fbioe.2015.00023.

4. Bundy J.G., Spurgeon D.J., Svendsen C., Hankard P.K., Osborn D., Lindon J.C., Nicholson J.K. Earthworm species of the genus Eisenia can be phenotypically differentiated by metabolic profiling. FEBS Letters. 2002;521(1-3):115-120. DOI 10.1016/s0014-5793(02) 02854-5.

5. Catchpole G., Beckmann M., Enot D., Mondhe M., Zywicki B., Taylor J., Fiehn O. Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc. Natl. Acad. Sci. 2005;102(40):1445814462. DOI 10.1073/pnas.0503955102.

6. Chong J., Soufan O., Li C., Caraus I., Li S., Bourque G., Wishart D., Xia J. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucl. Acids Res. 2018;46(1):486-494. DOI 10.1093/nar/gky310.

7. Farag M.A., Gad H.A., Heiss A.G., Wessjohann L.A. Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOF-MS and GC–MS coupled to chemometrics. Food Chem. 2014;151:333342. DOI 10.1016/j.foodchem.2013.11.032.

8. Fiehn O. Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics. 2001;2(3):155-168. DOI 10.1002/cfg.82.

9. Fiehn O. Metabolomics – the link between genotypes and phenotypes. Plant Mol. Biol. 2002;48:155-171. DOI 10.1007/978-94-010-04480_11.

10. Fiehn O., Kopka J., Dörmann P., Altmann T., Trethewey R., Willmitzer L. Metabolite profiling for plant functional genomics. Nat. Biotechnol. 2000;18(11):1157-1161. DOI 10.1038/81137.

11. Hall R., Beale M., Fiehn O., Hardy N., Sumner L., Bino R. Plant metabolomics: the missing link in functional genomics strategies. Plant Cell. 2002;14(7):1437-1440. DOI 10.1105/tpc.140720.

12. Kanani H., Chrysanthopoulos P.K., Klapa M.I. Standardizing GC–MS metabolomics. J. Chromatogr. B. Analyt. Technol. Biomed. Life Sci. 2008;871(2):191-201. DOI 10.1016/j.jchromb.2008.04.049.

13. Kanani H.H., Klapa M.I. Data correction strategy for metabolomics analysis using gas chromatography-mass spectrometry. Metab. Eng. 2007;9(1):39-51. DOI 10.1016/j.ymben.2006.08.001.

14. Lisec J., Schauer N., Kopka J., Willmitzer L., Fernie A.R. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 2006;1(1):387-396. DOI 10.1038/nprot.2006.59.

15. Maharjan R.P., Ferenci T. Global metabolite analysis: the influence of extraction methodology on metabolome profiles of escherichia coli. Anal. Biochem. 2003;313(1):145-154. DOI 10.1016/S0003-2697(02) 00536-5.

16. Martineau E., Tea I., Loaëc G., Giraudeau P., Akoka S. Strategy for choosing extraction procedures for NMR-based metabolomic analysis of mammalian cells. Anal. Bioanal. Chem. 2011;401(7):21332142. DOI 10.1007/s00216-011-5310-y.

17. Puzanskiy R.K., Yemelyanov V.V., Kliukova M.S., Shavarda A.L., Shtark O.Y., Yurkov A.P., Shishova M.F. Optimization of metabolite profiling for Black Medick (Medicago lupulina) and Peas (Pisum sativum). Applied Biochem. Microbiol. 2018;54(4):442-448. DOI 10.1134/S0003683818040129.

18. Roessner U., Luedemann A., Brust D., Fiehn O., Linke T., Willmitzer L., Fernie A.R. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. The Plant Cell. 2001;13(1):11-29. DOI 10.1105/tpc.13.1.11.

19. Röhlig R.M., Eder J., Engel K.H. Metabolite profiling of maize grain: differentiation due to genetics and environment. Metabolomics. 2009;5(4):459-477. DOI 10.1007/s11306-009-0171-5.

20. Shinbo Y., Nakamura Y., Altaf-Ul-Amin M., Asahi H., Kurokawa K., Arita M., Kanaya S. KNApSAcK: a comprehensive species-metabolite relationship database. Plant Metabolomics. 2006;57:165-181. DOI 10.1007/3-540-29782-0_13.

21. Wishart D.S. Advances in metabolite identification. Bioanalysis. 2011; 3(15):1769-1782. DOI 10.4155/bio.11.155


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