Literature DB >> 16460820

Unintended effects in genetically modified crops: revealed by metabolomics?

Heiko Rischer1, Kirsi-Marja Oksman-Caldentey.   

Abstract

In Europe the commercialization of food derived from genetically modified plants has been slow because of the complex regulatory process and the concerns of consumers. Risk assessment is focused on potential adverse effects on humans and the environment, which could result from unintended effects of genetic modifications: unintended effects are connected to changes in metabolite levels in the plants. One of the major challenges is how to analyze the overall metabolite composition of GM plants in comparison to conventional cultivars, and one possible solution is offered by metabolomics. The ultimate aim of metabolomics is the identification and quantification of all small molecules in an organism; however, a single method enabling complete metabolome analysis does not exist. Given a comprehensive extraction method, a hierarchical strategy--starting with global fingerprinting and followed by complementary profiling attempts--is the most logical and economic approach to detect unintended effects in GM crops.

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Year:  2006        PMID: 16460820     DOI: 10.1016/j.tibtech.2006.01.009

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  7 in total

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4.  Increased Levels of Antinutritional and/or Defense Proteins Reduced the Protein Quality of a Disease-Resistant Soybean Cultivar.

Authors:  Daniele O B Sousa; Ana F U Carvalho; José Tadeu A Oliveira; Davi F Farias; Ivan Castelar; Henrique P Oliveira; Ilka M Vasconcelos
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Authors:  Arnaud Bovy; Elio Schijlen; Robert D Hall
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6.  From metabolome to phenotype: GC-MS metabolomics of developing mutant barley seeds reveals effects of growth, temperature and genotype.

Authors:  Bekzod Khakimov; Morten Arendt Rasmussen; Rubini Maya Kannangara; Birthe Møller Jespersen; Lars Munck; Søren Balling Engelsen
Journal:  Sci Rep       Date:  2017-08-15       Impact factor: 4.379

7.  Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait.

Authors:  George G Harrigan; Tyamagondlu V Venkatesh; Mark Leibman; Jonathan Blankenship; Timothy Perez; Steven Halls; Alexander W Chassy; Oliver Fiehn; Yun Xu; Royston Goodacre
Journal:  Metabolomics       Date:  2016-03-15       Impact factor: 4.290

  7 in total

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