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Sample Set Information

Title Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment
Description We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that w92% had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms.
Authors Miyako Kusano, Henning Redestig, Tadayoshi Hirai, Akira Oikawa, Fumio Matsuda, Atsushi Fukushima, Masanori Arita, Shin Watanabe, Megumu Yano, Kyoko Hiwasa-Tanase, Hiroshi Ezura, Kazuki Saito
Reference Kusano M et al. (2011) PLOS ONE 6: e16989

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The raw data files are available at DROP Met web site in PRIMe database of RIKEN.

Data Analysis Details Information

Title MassLynx and MetAlign
Description The profiling data files recorded in the MassLynx format (raw) were converted to the NetCDF format using the DataBridge function of MassLynx 4.1. From the set of NetCDF data files, the data matrix was generated using the MetAlign software (De Vos et al., 2007). By using this procedure, the data matrixes with unit mass data were generated. The data matrices were processed using in-house software written in Perl/Tk. The original peak intensity values were divided with that of the internal standards (lidocaine at m/z 235 [M + H]+ and (-)-camphor-10-sulfonic acid at m/z 231 [M - H]- for the positive and negative ion modes, respectively) determined in the same samples to normalize the peak intensity values among the metabolic profile data.

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