From models to crop species: caveats and solutions for translational metabolomics

• Main Authors: Takayuki eTohge, Tabea eMettler, Stephanie eArrivault, Adam James Carroll, Mark eStitt, Alisdair eFernie
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2011-10-01
• Series: Frontiers in Plant Science
• Subjects: LC-MS; sample preparation; Chemical diversity; Ion suppression; Plant metabolomics; Translational biology
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fpls.2011.00061/full

Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa) that illustrate how such dangers can be detected and circumvented.