title: Using metabolomics to estimate unintended effects in transgenic crop plants: problems, promises, and opportunities.
abstract: Transgenic crops are widespread in some countries and sectors of the agro-economy, but are also highly contentious. Proponents of transgenic crop improvement often cite the "substantial equivalence" of transgenic crops to the their nontransgenic parents and sibling varieties. Opponents of transgenic crop improvement dismiss the substantial equivalence standard as being without statistical basis and emphasize the possible unintended effects to food quality and composition due to genetic transformation. Systems biology approaches should help consumers, regulators, and other stakeholders make better decisions regarding transgenic crop improvement by characterizing the composition of conventional and transgenically improved crop species and products. In particular, metabolomic profiling via mass spectrometry and nuclear magnetic resonance can make broad and deep assessments of food quality and content. The metabolome observed in a transgenic variety can then be assessed relative to the consumer and regulator accepted phenotypic range observed among conventional varieties. I briefly discuss both targeted (closed architecture) and nontargeted (open architecture) metabolomics with respect to the transgenic crop debate and highlight several challenges to the field. While most experimental examples come from tomato (Solanum lycoperiscum), analytical methods from all of systems biology are discussed.
authors.affiliation: Robert W Holley Center for Agriculture and Health, USDA-ARS, Ithaca, NY 14853, USA. Owen.Hoekenga@ars.usda.gov
authors.forename: Owen A
authors.initials: OA
authors.lastname: Hoekenga
mesh_terms: D001709:Biotechnology; D005818:Genetic Engineering / Q000009:adverse effects / Q000379:methods / Q000592:standards / Q000639:trends; D018551:Solanum lycopersicum / Q000009:adverse effects / Q000235:genetics / Q000378:metabolism; D055432:Metabolomics / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D010945:Plants, Edible / Q000009:adverse effects* / Q000235:genetics / Q000378:metabolism*; D030821:Plants, Genetically Modified / Q000009:adverse effects* / Q000235:genetics / Q000378:metabolism; D049490:Systems Biology