Metabolite profiling of maize kernels-genetic modification versus environmental influence

Thomas Frank, Richard M. Röhlig, Howard V. Davies, Eugenia Barros, Karl Heinz Engel

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

A metabolite profiling approach based on gas chromatography-mass spectrometry (GC-MS) was applied to investigate the metabolite profiles of genetically modified (GM) Bt-maize (DKC78-15B, TXP 138F) and Roundup Ready-maize (DKC78-35R). For the comparative investigation of the impact of genetic modification versus environmental influence on the metabolite profiles, GM maize was grown together with the non-GM near-isogenic comparators under different environmental conditions, including several growing locations and seasons in Germany and South Africa. Analyses of variance (ANOVA) revealed significant differences between GM and non-GM maize grown in Germany and South Africa. For the factor genotype, 4 and 3%, respectively, of the total number of peaks detected by GC-MS showed statistically significant differences (p < 0.01) in peak heights as compared to the respective isogenic lines. However, ANOVA for the factor environment (growing location, season) revealed higher numbers of significant differences (p < 0.01) between the GM and the non-GM maize grown in Germany (42%) and South Africa (10%), respectively. This indicates that the majority of differences observed are related to natural variability rather than to the genetic modifications. In addition, multivariate data assessment by means of principal component analysis revealed that environmental factors, that is, growing locations and seasons, were dominant parameters driving the variability of the maize metabolite profiles.

Original languageEnglish
Pages (from-to)3005-3012
Number of pages8
JournalJournal of agricultural and food chemistry
Volume60
Issue number12
DOIs
StatePublished - 28 Mar 2012

Keywords

  • Bt-maize
  • Roundup Ready maize
  • gas chromatography
  • metabolite profiling
  • natural variability
  • safety assessment

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