1H-NMR metabolomics: Profiling method for a rapid and efficient screening of transgenic plants

  • Yosra Ben Akal-Ben Fatma
  • Katia Pianelli
  • Martine Dieuaide-Noubhani
  • Aline Le Menn
  • Catherine Deborde
  • Mickaël Maucourt
  • Marie-Hélène Andrieu
  • Dominique Rolin
  • Christophe Rothan
  • Annick Moing
  • Sadok Bouzid
  • Cécile Cabasson
Keywords: Metabolome, GMO, tomato, fruit, 1H-NMR profiling, screening


Metabolomics-based approaches are methods of choice for studying changes in fruit composition induced by  environmental or genetic modulation of biochemical pathways in the fruit. Owing to enzyme redundancy and  high plasticity of the metabolic network, transgenic alteration of the activity of the enzymes from the central metabolism very often results in only slight modifications of the fruit composition. In order to avoid costly and  time-consuming plant analysis, we used a fast and sensitive 1H-NMR-based metabolomic profiling technique  allowing discovery of slight metabolite variations in a large number of samples. Here, we describe the  screening of transgenic tomato plants in which two genes from the central metabolism, phosphoenolpyruvate  carboxylase (EC. and malate synthase (EC were silenced by antisens and RNAi strategy.  1H-NMR metabolomic profiles of methanol-d4 D2O buffer extracts of tomato fruit flesh were acquired and  subjected to unsupervised multivariate statistical analysis. 1H-NMR spectra were binned into variable-size  spectral domains, making it possible to get an overall analysis of a large number of resonances, even in the  case of uncontrolled variation of the chemical shift. Principal component analysis was used to separate groups  of samples and to relate known and unknown metabolites to transgenic events. The screening of 100 samples,  from extraction to data mining, took 36 h. Thus, this procedure allows the rapid selection of metabolic  phenotypes of interest among about 30 transgenic lines.

Key words: Metabolome, GMO, tomato, fruit, 1H-NMR profiling, screening.


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eISSN: 1684-5315