Skip to main content
SpringerLink
Log in

Metabolite profiling of maize grain: differentiation due to genetics and environment

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

A comparative metabolite profiling approach based on gas chromatography-mass spectrometry (GC/MS) was applied to investigate the impact of genetic background, growing location and season on the chemical composition of maize grain. The metabolite profiling protocol involved sub-fractionation of the metabolites and allowed the assessment of about 300 distinct analytes from different chemical classes (polar to lipophilic), of which 167 could be identified. A comparison, over three consecutive growing seasons, of the metabolite profiles of four maize cultivars which differed in their maturity classification, was carried out using principal component analysis (PCA). This revealed a strong separation of one cultivar in the first growing season, which could be explained by the immaturity of the kernels of this cultivar compared with others in the field trial. Further evaluations by pair-wise comparison using Student’s t-test and analysis of variance (ANOVA) showed that the growing season was the most prominent impact factor driving variation of the metabolite pool. An increased understanding of metabolic variation was achieved by analysis of a second sample set comprising one cultivar grown for 3 years at four locations. The applied GC/MS-based metabolite profiling demonstrated the natural variation in maize grain metabolite pools resulting from the interplay of environment, season, and genotype.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Arruda, P., da Silva, W. J., & Teixeira, J. P. F. (1978). Protein and free amino acids in a high lysine maize double mutant. Phytochemistry, 17, 1217–1218.

    Article  CAS  Google Scholar 

  • Ashton, W. D. (1972). The Logit Transformation with special reference to its uses in bioassay. London: Charles Griffin & Company Limited.

    Google Scholar 

  • Ausloos, P., Clifton, C. L., Lias, S. G., Mikaya, A. I., Stein, S. E., Tchekhovskoi, D. V., et al. (1999). The critical evaluation of a comprehensive mass spectral library. Journal of the American Society for Mass Spectrometry, 10, 287–299.

    Article  CAS  PubMed  Google Scholar 

  • Bundessortenamt. (2008). Beschreibende Sortenliste - Getreide, Mais, Ölfrüchte, Leguminosen (großkörnig), Hackfrüchte 2008 (außer Kartoffeln). Hannover: Bundessortenamt.

    Google Scholar 

  • Castro, C., & Manetti, C. (2007). A multiway approach to analyze metabonomic data: a study of maize seeds development. Analytical Biochemistry, 371, 194–200.

    Article  CAS  PubMed  Google Scholar 

  • Daftary, R. D., & Pomeranz, Y. (1965). Changes in lipid composition in maturing wheat. Journal of Food Science, 30, 577–582.

    Article  CAS  Google Scholar 

  • Duvick, D. N. (1952). Free amino acids in the developing endosperm of maize. American Journal of Botany, 39, 656–661.

    Article  CAS  Google Scholar 

  • FAO (2005) ProdSTAT: Crops, food and agriculture organization of the United Nations.

  • Fernie, A. R., & Schauer, N. (2008). Metabolomics-assisted breeding: a viable option for crop improvement? Trends in Genetics, 25, 39–48.

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Fiehn, O. (2002). Metabolomics—the link between genotypes and phenotypes. Plant Molecular Biology, 48, 155–171.

    Article  CAS  PubMed  Google Scholar 

  • Fiehn, O., Kopka, J., Dormann, P., Altmann, T., Trethewey, R. N., & Willmitzer, L. (2000). Metabolite profiling for plant functional genomics. Nature Biotechnology, 18, 1157–1161.

    Article  CAS  PubMed  Google Scholar 

  • Frank, T., Meuleye, B. S., Miller, A., Shu, Q.-Y., & Engel, K.-H. (2007). Metabolite profiling of two low phytic acid (lpa) rice mutants. Journal of Agricultural and Food Chemistry, 55, 11011–11019.

    Article  CAS  PubMed  Google Scholar 

  • Frenzel, T., Miller, A., & Engel, K.-H. (2002). Metabolite profiling-a fractionation method for analysis of major and minor compounds in rice grains. Cereal Chemistry, 79, 215–221.

    Article  CAS  Google Scholar 

  • Frenzel, T., Miller, A., & Engel, K.-H. (2003). A methodology for automated comparative analysis of metabolite profiling data. European Food Research and Technology, 216, 335–342.

    CAS  Google Scholar 

  • Greiff, W. R., Morgan, W. T., & Ponte, J. M. (2002). The role of variance in term weighting for probabilistic information retrieval. Proceedings of the Eleventh International Conference on Information and Knowledge Management, ACM.

  • Harrigan, G. G., Stork, L. G., Riordan, S. G., Reynolds, T. L., Ridley, W. P., Masucci, J. D., et al. (2007a). Impact of genetics and environment on nutritional and metabolite components of maize grain. Journal of Agricultural and Food Chemistry, 55, 6177–6185.

    Article  CAS  PubMed  Google Scholar 

  • Harrigan, G. G., Stork, L. G., Riordan, S. G., Ridley, W. P., MacIsaac, S., Halls, S. C., et al. (2007b). Metabolite analyses of grain from maize hybrids grown in the United States under drought and watered conditions during the 2002 field season. Journal of Agricultural and Food Chemistry, 55, 6169–6176.

    Article  CAS  PubMed  Google Scholar 

  • Hazebroek, J., Harp, T., Shi, J., & Wang, H. (2007). Metabolomic analysis of low phytic acid maize kernels. In B. J. Nikolau & E. S. Wurtele (Eds.), Concepts in plant metabolomics (pp. 221–237). Berlin, Germany: Springer.

    Chapter  Google Scholar 

  • Hirel, B., Andrieu, B., Valadier, M.-H., Renard, S., Quilleré, I., Chelle, M., et al. (2005). Physiology of maize II: Identification of physiological markers representative of the nitrogen status of maize (Zea mays) leaves during grain filling. Physiologia Plantarum, 124, 178–188.

    Article  CAS  Google Scholar 

  • IPS, Institut für Pflanzenschutz (2009). Agrarmeteorologisches Messnetz Bayern, Bayerische Landesanstalt für Landwirtschaft (LfL).

  • Jackson, J. E. (1991). A user’s guide to principal components. New York: Wiley.

    Book  Google Scholar 

  • Kamal-Eldin, A., Appelqvist, L. Å., Yousif, G., & Iskander, G. M. (1992). Seed lipids of Sesamum indicum and related wild species in Sudan. The sterols. Journal of the Science of Food and Agriculture, 59, 327–334.

    Article  CAS  Google Scholar 

  • Kopka, J., Schauer, N., Krueger, S., Birkemeyer, C., Usadel, B., Bergmuller, E., et al. (2005). GMD@CSB.DB: The Golm Metabolome Database. Bioinformatics, 21, 1635–1638.

    Article  CAS  PubMed  Google Scholar 

  • Lozovaya, V., Ulanov, A., Lygin, A., Duncan, D., & Widholm, J. (2006). Biochemical features of maize tissues with different capacities to regenerate plants. Planta, 224, 1385–1399.

    Article  CAS  PubMed  Google Scholar 

  • Meyna, S. (2005). Freie und triglycerid-gebundene Hydroxyfettsäuren in Gerste und Malz und ihre Bedeutung für die Geschmacksstabilität des Bieres, Fakultät III (Prozesswissenschaften), Technische Universität Berlin, pp. 126.

  • Miller, L. T. (1982). Single derivatization method for routine analysis of bacterial whole-cell fatty acid methyl esters, including hydroxy acids. Journal of Clinical Microbiology, 16, 584–586.

    CAS  PubMed  Google Scholar 

  • Miyanishi, T., Tutimoto, S., Ogura, M., & Iio, T. (1991). Studies on the taste and flavor of sweet corn. I. Changes in chemical components in sweet corn (cv. Golden Earlipak) kernels during maturation. Nippon Shokuhin Kogyo Gakkaishi, 38, 758–764.

    CAS  Google Scholar 

  • Reynolds, T. L., Nemeth, M. A., Glenn, K. C., Ridley, W. P., & Astwood, J. D. (2005). Natural variability of metabolites in maize grain: Differences due to genetic background. Journal of Agricultural and Food Chemistry, 53, 10061–10067.

    Article  CAS  PubMed  Google Scholar 

  • Ridley, W. P., Sidhu, R. S., Pyla, P. D., Nemeth, M. A., Breeze, M. L., & Astwood, J. D. (2002). Comparison of the nutritional profile of glyphosate-tolerant corn event NK603 with that of conventional corn (Zea mays L.). Journal of Agricultural and Food Chemistry, 50, 7235–7243.

    Article  CAS  PubMed  Google Scholar 

  • Roessner, U., Wagner, C., Kopka, J., Trethewey, R. N., & Willmitzer, L. (2000). Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant Journal, 23, 131–142.

    Article  CAS  PubMed  Google Scholar 

  • Scherz, H., & Senser, F. (2000). Food composition and nutrition tables (6th ed.). Stuttgart, Germany: Medpharm Scientific Publication, CRC Press.

    Google Scholar 

  • Seebauer, J. R., Moose, S. P., Fabbri, B. J., Crossland, L. D., & Below, F. E. (2004). Amino acid metabolism in maize earshoots. Implications for assimilate preconditioning and nitrogen signaling. Plant Physiology, 136, 4326–4334.

    Article  CAS  PubMed  Google Scholar 

  • Ter Braak, C. J. F., & Gremmen, N. J. M. (1987). Ecological amplitudes of plant species and the internal consistency of Ellenberg’s indicator values for moisture. Plant Ecology, 69, 79–87.

    Article  Google Scholar 

  • Voelker, T., & Kinney, A. J. (2001). Variations in the biosynthesis of seed-storage lipids. Annual Review of Plant Physiology and Plant Molecular Biology, 52, 335–361.

    Article  CAS  PubMed  Google Scholar 

  • Weber, E. J. (1969). Lipids of maturing grain of corn (Zea mays). I. Changes in lipid classes and fatty acid composition. Journal of the American Oil Chemists’ Society, 46, 485–488.

    Article  CAS  PubMed  Google Scholar 

  • Wendland, M., Diepolder, M., & Capriel, P. (2007). Leitfaden für die Düngung von Acker- und Grünland. Bayerische Landesanstalt für Landwirtschaft (LfL).

  • Xu, Z., & Godber, J. S. (1999). Purification and identification of components of γ-Oryzanol in rice bran oil. Journal of Agricultural and Food Chemistry, 47, 2724–2728.

    Article  CAS  PubMed  Google Scholar 

  • Young, T. E., & Gallie, D. R. (2000). Programmed cell death during endosperm development. Plant Molecular Biology, 44, 283–301.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was financially supported by the EU FP6 project SAFEFOODS (contract no. Food-CT-2004-506446, Promoting Food Safety through a New Integrated Risk Analysis Approach for Foods—SAFEFOODS). The technical assistance by Martina Denk is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Lehrstuhl für Allgemeine Lebensmitteltechnologie, Technische Universität München, Am Forum 2, D-85350, Freising-Weihenstephan, Germany

    Richard M. Röhlig & Karl-Heinz Engel

  2. Institut für Pflanzenbau und Pflanzenzüchtung, Bayerische Landesanstalt für Landwirtschaft, Am Gereuth 8, D-85354, Freising, Germany

    Joachim Eder

Authors
  1. Richard M. Röhlig
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joachim Eder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karl-Heinz Engel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Karl-Heinz Engel.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (XLS 26 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Röhlig, R.M., Eder, J. & Engel, KH. Metabolite profiling of maize grain: differentiation due to genetics and environment. Metabolomics 5, 459–477 (2009). https://doi.org/10.1007/s11306-009-0171-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-009-0171-5

Keywords

Search

Navigation